Updated on 2024/04/04

写真a

 
TAKEDA, Kazuya
 
Organization
Institutes of Innovation for Future Society Mobility Research Course Professor
Graduate School of Information Science Professor
Graduate School of Informatics Professor
Graduate School
Graduate School of Information Science
Graduate School of Informatics
Undergraduate School
School of Engineering
Title
Professor
Contact information
メールアドレス

Degree 1

  1. Ph.D. (Engineering) ( 1993.9   Nagoya University ) 

Research Interests 6

  1. Signal Processing for Acoustic, Speech, Spoken Language and Behavior

  2. Human Machine Interaction

  3. group behavior of sports

  4. Intelligent vehicle

  5. Large signal corpus

  6. ドライバモデル

Research Areas 3

  1. Others / Others  / Intelligent Informatics

  2. Others / Others  / Information and Communication Engineering

  3. Informatics / Intelligent informatics  / human behaviro signal information processing

Current Research Project and SDGs 4

  1. Modeling and Prediction of Driving Behavior

  2. Information Processing of Speech and Acoustic Signals

  3. Human/Machin Interaction

  4. Information processing of sport behavior signals

Research History 12

  1. Nagoya University   Director

    2020.4

  2. Nagoya University   Institute of Innovation for Future Society Mobility Research Course

    2019.4 - 2020.3

  3. Nagoya University   Sch. of Informatics, dept. of Intelligent Systems   Professor

    2017.4

  4. Nagoya University   Leading Graduate School Promotion Department   Professor

    2014.4

  5. Nagoya University   Graduate School of Informatics   Professor

    2014.4

  6. Nagoya University   Green Mobility Collaborative Research Center Green Mobility Collaborative Research Center

    2011.7 - 2017.3

  7. Nagoya University   Innovative Research Center for Preventive Medical Engineering

    2010.4

  8. 名古屋大学 大学院・情報科学研究科・メディア科学専攻   教授

    2003.4

  9. Associate Professor, School/ Graduate School of Engineering, Nagoya University

    1995.4 - 2003.3

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    Country:Japan

  10. 名古屋大学 工学部・工学研究科   助教授

    1995.4

  11. Supervisor, KDD Research and Development Laboratories

    1990.2 - 1995.3

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    Country:Japan

  12. Researcher, Speech Information Processing Laboratory, Advanced Telecommunication Research Laboratores

    1986.7 - 1990.2

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    Country:Japan

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Education 2

  1. Nagoya University   Graduate School, Division of Engineering

    1983.4 - 1985.3

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    Country: Japan

  2. Nagoya University   Faculty of Engineering   Department of Electronics and Electric Engineering

    1979.4 - 1983.3

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    Country: Japan

Professional Memberships 40

  1. 日本音響学会   (理事、副会長、支部長等を歴任)

    1983.9

  2. IEEE   (Served as Society BoG (3), Chapter Chairs (2))

    2014.1

  3. The Institute of Electronics, Information and Communication Engineers   member/ Senior member

    1987.6

  4. Information Processing Society of Japan   member

    1994.6

  5. 自動車技術会   会員

    2012.4

  6. ロボット学会   会員

    2014.4

  7. 電子情報通信学会   音声研究会研究専門委員

    2009.4 - 2013.3

  8. 日本音響学会   東海支部 評議員

    2005.5

  9. 電子情報通信学会   論文誌特集号編集長

    2007.1 - 2008.8

  10. 電子情報通信学会   ISS和文論文誌(D)編集長

    2008.8 - 2010.5

  11. IEEE   Member/ Senior Member

    1997.3

  12. The Acoustic Society of Japan   member

    1984.6

  13. Information Processing Society Japan   Chair for SIG Spoken Language Processing

    2006.4 - 2009.3

  14. 情報処理学会   音声言語情報処理研究会 研究連絡委員

    2008.4 - 2010.5

  15. 情報処理学会   論文誌特集号編集委員 音声ドキュメント処理

    2007.9 - 2009.2

  16. 情報処理学会   論文誌特集号編集委員

    2007.5 - 2008.8

  17. 情報処理学会   代表委員

    2007.4 - 2009.3

  18. Institute of Electrical and Electronics Engineers   Secretary, Signal Processing Society Japan Chapter

    2007.1 - 2008.12

  19. Acousitical Sociery Japan   Exective board member

    2006.5 - 2009.4

  20. The Institute of Electronics, Information and Communication Engineers   Borad member of editorial committee

    2006.5 - 2008.4

  21. Institute of Electrical and Electronics Engineers   Standing Committee Chair for student activities, Nagoya Section

    2005.1 - 2006.12

  22. Information Processing Society Japan   Borad member for SIG Spoken Language Processing

    2004.4 - 2007.3

  23. The Institute of Electronics, Information and Communication Engineers   Associate Editor

    2004.4 - 2007.3

  24. 情報処理学会   音声言語情報処理研究会 幹事

    2004.4 - 2006.6

  25. 情報処理学会   音声言語情報処理研究会 音声認識コンソーシアム 実行幹事

    2001.1 - 2003.10

  26. 電子情報通信学会   音声研究会幹事

    2000.5 - 2002.4

  27. GSK(言語資源コンソーシアム)   運営委員

    1999.5 - 2001.4

  28. 映像情報メディア学会   マルチメディア情報処理研究委員会委員

    1999.5 - 2001.4

  29. Acousitical Sociery Japan   member of editorial committee

    1999.4 - 2004.3

  30. 日本音響学会   東海支部 庶務幹事

    1998.5 - 2001.4

  31. 日本音響学会   データベース技術委員会 委員

    1996.5 - 2001.4

  32. 情報処理学会   音声言語情報処理研究会 研究連絡委員

    1996.4 - 2000.3

  33. Information Processing Society Japan   Committee member for SIG Spoken Language Processing

    1996.4 - 1999.3

  34. 情報処理学会   音声言語情報処理研究会 大規模連続音声データベースWG 幹事

    1996.4 - 1998.3

  35. Acousitical Sociery Japan   Reviewer

    1995.4

  36. The Institute of Electronics, Information and Communication Engineers   board member of Speech Technical Group

    1994.5 - 1996.4

  37. The Institute of Electronics, Information and Communication Engineers   Reviewer

    1993.4

  38. IEEE

  39. 日本音響学会

  40. 情報処理学会

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Committee Memberships 39

  1. IEEE Intelligent Transportation Systems (ITS) Society   member of the Board of Governors (BoG)  

    2014.1 - 2022.12   

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    Committee type:Academic society

  2. IEEE Signal Processing Society   Tokyo Joint Chapter Chair  

    2019.1 - 2020.12   

  3. IEEE Intelligent Transportation Systems (ITS) Society   Nagoya Chapter Chair  

    2021.1 - 2022.12   

  4. ITU-T FG Distraction   Vice Chair  

    2011.8 - 2013.3   

  5. 日本音響学会   理事・副会長(2017.5-2019.4)  

    2017.5 - 2021.4   

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    Committee type:Academic society

  6. Asia Pacific Signal Information Processing Association   member of BOG (Board of Goveners)  

    2019.1 - 2022.12   

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    Committee type:Academic society

  7. 科学研究費委員会専門委員会   専門委員  

    2017.12 - 2018.11   

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    Committee type:Government

  8. 交通事故低減詳細効果見積のためのシミュレーション技術の開発及び実証 開発検討委員会   委員  

    2017.6 - 2018.3   

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    Committee type:Government

  9. 名古屋市教育委員会 SSH運営指導委員会   委員  

    2017.5   

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    Committee type:Municipal

  10. IEEE Intelligent Transportation Society   member of Board of Governors (BoG)  

    2013.1 - 2021.12   

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    Committee type:Academic society

  11. 名古屋産科学研究所 次世代自動車地域産学官フォーラム・産学連携プロジェクト化研究会   委員  

    2011.8 - 2015.3   

  12. 名古屋市教育委員会 魅力ある高等学校づくり推進研究協議会   副会長  

    2011.7 - 2016.3   

  13. 科学技術振興機構 研究成果最適展開支援プログラム専門委員会   専門委員  

    2011.5 - 2017.3   

  14. International Advisory Board, SAFER project, Chalmers Technological University   member  

    2010.9   

  15. IEEE International Conference on Acoustic Speech and Signal Processing (ICASSP 2012)   Organizing Committee member, Special Session co-chair  

    2010.3 - 2012.5   

  16. First International Conference on Future Active Safety Technology fast-ZERO'11   Organizing Committee member  

    2009.9 - 2011.9   

  17. The 5th Biennal Workshop on Digital Signal Processing for In-Vehicle Systems   Workshop Co-Chair  

    2009.9 - 2011.9   

  18. 名古屋産科学研究所 CHC企画運営委員会   委員  

    2009.7   

  19. 名古屋産業科学研究所   非常勤所員  

    2009.4   

  20. 愛知県公害審査委員会   委員  

    2008.11 - 2017.3   

  21. ISCA Interspeech 2010   Organizing Committee member, Industrial Exhibision co-chair  

    2008.9 - 2010.9   

  22. IEEE International Conference on Vehicular Electronics System, (ICVES 2009)   Technical Program Committee, co-chair  

    2008.7 - 2009.11   

  23. International Conference on Pattern Recognition 2010   Track Co-Chair (Editor)  

    2008.6 - 2010.6   

  24. IEEE Intelligent Vehicle Sympsium 2010, IV'10   TPC member (Associate Editor)  

    2008.6 - 2010.6   

  25. Biennial on DSP for in-Vehicle and Mobile Systems   Workshop co-chair  

    2008.6 - 2009.6   

  26. 国立情報学研究所 音声データベース推進委員会   委員  

    2008.4   

  27. 情報通信研究機構 外部評価委員会   委員  

    2008.4 - 2011.3   

  28. 科学技術振興機構「科学技術・学術審議会研究評価部会」評価作業部会   委員  

    2007.9 - 2009.3   

  29. Biennial on DSP for in-Vehicle and Mobile Systems   Workshop Co-Chair  

    2006.4 - 2007.6   

  30. 2007 IEEE Automatic Speech Recognition and Understanding Workshop   Demo Session Chair  

    2005.12 - 2007.12   

  31. The 9th ACM International Conference on Multimodal Interfaces (ICMI' 07)   Technical Program Co-Chair  

    2005.4 - 2007.10   

  32. Biennial on DSP for in-Vehicle and Mobile Systems   Co-Chair  

    2004.4 - 2005.9   

  33. Workshop on Real World Corpora in Mobile Environment (RWCinME)   Secretary General  

    2004.4 - 2005.4   

  34. 総務省「戦略的情報通信研究開発推進制度」専門評価委員会   専門評価委員  

    2002.6   

  35. ISCA & IEEE Workshop on Spontaneous Speech Processing and Recognition (SSPR)   International Scientific Committee member  

    2002.4 - 2003.4   

  36.   Organizing Committee Member  

    2000.7 - 2001.4   

  37. 2004 International Congress on Acoustics (ICA2004)   Program Committee Secretary  

    1998.10 - 2004.10   

  38. Second IEEE Workshop on Interactive Voice Technology for Telecommunications Applications (IVTTA 94)   Publication Committee Chair  

    1993.6 - 1994.9   

  39. 基盤技術研究促進センター   成果管理評価委員  

    1991.10 - 1992.5   

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Awards 16

  1. Best Poster Award

    2022.11   ACM SIGSPATIAL 2022   Estimating counterfactual treatment outcomes over time in complex multi-vehicle simulation

    Keisuke Fujii, Koh Takeuchi, Atsushi Kuribayashi, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda

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    Award type:Award from international society, conference, symposium, etc.  Country:United States

  2. 優秀発表賞

    2022.10   日本スポーツ心理学会第49回大会   深層強化学習を用いた最適な協調行動およびその基盤となる認知・意思決定機構の探究

    筒井和詩, 武田一哉

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  3. Honorable Mention Award

    2021.8   13th International ACM Conference on Automotive User Interfaces   Automatic Generation of Road Trip Summary Video for Reminiscence and Entertainment using Dashcam Video

    Kana Bito, Itiro Siio, Yoshio Ishiguro, Kazuya Takeda

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    Award type:Award from international society, conference, symposium, etc. 

  4. IEEE ITS Society Outstanding Research Award

    2020.9   IEEE ITS Society   Contributions to Data centric Driving Behavior Modeling

    Kazuya Takeda

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    Award type:International academic award (Japan or overseas)  Country:Japan

  5. 第12回 Journal of Robotics and Mechatronics 優秀論文賞

    2020.1   Fuji technology press  

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    Award type:Honored in official journal of a scientific society, scientific journal  Country:Japan

  6. Best Paper Award at 19th International Conference on Intelligent Transportation Systems (ITSC2016) IEEE ITS Society November 2016

    2016.11   IEEE ITS Society   Compressing Continuous Point Cloud Data using Image Compression Methods

    Chenxi Tu, Eijiro Takeuchi, Chiyomi Miyajima and Kazuya Takeda

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    Award type:Award from international society, conference, symposium, etc.  Country:Japan

  7. 平成21年度 情報処理学会 ITS研究会優秀論文

    2009.12   情報処理学会  

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    Country:Japan

    西脇由博、宮島千代美、北岡教英、武田一哉

  8. ICVES 2009 Best Conference Paper Award(IEEE International Conference on Vehicular Electronics and Safety)

    2009.11   Technical Program Committee of IEEE International Conference on Vehicular Electronics and Safety  

  9. 平成21年度日本音響学会秋季大会ポスター賞

    2009.9   日本音響学会  

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    Country:Japan

    森本泰子

  10. Best Paper Award on IEEE 2008 International Workshop on Multimedia Signal Processing

    2008.10   IEEE 2008 International Workshop on Multimedia Signal Processing  

  11. 情報学ワークショップ(WiNF2007)優秀論文賞

    2007.9   情報学ワークショップ(WiNF2007)  

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    Country:Japan

    自由視聴点TVのための自由聴点音場の構成方法丹羽健太,西野隆典,武田一哉

  12. 日本音響学会2008年春季研究発表会ポスター賞

    2007.9   日本音響学会  

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    Country:Japan

    丹羽健太

  13. 情報処理学会音楽情報科学研究会 『夏のシンポジウム2007』 ベストプレゼンテーション賞

    2007.8   情報処理学会音楽情報科学研究会  

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    Country:Japan

    情報処理学会音楽情報科学研究会 『夏のシンポジウム2007』 ベストプレゼンテーション賞歌声の旋律と動的変動を特徴づけた確率モデルに関する検討大石康智, 後藤真孝, 伊藤克亘, 武田一哉

  14. 電子情報通信学会論文賞

    2001  

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    Country:Japan

  15. 日本音響学会技術開発賞

    1995  

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    Country:Japan

  16. 粟屋潔学術奨励賞

    1993  

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    Country:Japan

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Papers 671

  1. Decentralized policy learning with partial observation and mechanical constraints for multiperson modeling

    Fujii, K; Takeishi, N; Kawahara, Y; Takeda, K

    NEURAL NETWORKS   Vol. 171   page: 40 - 52   2024.3

  2. L-DIG: A GAN-Based Method for LiDAR Point Cloud Processing under Snow Driving Conditions

    Zhang, YX; Ding, M; Yang, HT; Niu, YJ; Feng, Y; Ohtani, K; Takeda, K

    SENSORS   Vol. 23 ( 21 )   2023.11

  3. Controllable Unsupervised Snow Synthesis by Latent Style Space Manipulation

    Yang, HT; Carballo, A; Zhang, YX; Takeda, K

    SENSORS   Vol. 23 ( 20 )   2023.10

  4. Estimation of control area in badminton doubles with pose information from top and back view drone videos Reviewed

    Ding Ning, Takeda Kazuya, Jin Wenhui, Bei Yingjiu, Fujii Keisuke

    MULTIMEDIA TOOLS AND APPLICATIONS     2023.8

  5. Pitching strategy evaluation via stratified analysis using propensity score Reviewed

    Nakahara Hiroshi, Takeda Kazuya, Fujii Keisuke

    JOURNAL OF QUANTITATIVE ANALYSIS IN SPORTS     2023.5

  6. Localization System for Vehicle Navigation Based on GNSS/IMU Using Time-Series Optimization with Road Gradient Constrain

    Takanose Aoki, Kondo Kaito, Hoda Yuta, Meguro Junichi, Takeda Kazuya

    JOURNAL OF ROBOTICS AND MECHATRONICS   Vol. 35 ( 2 ) page: 387 - 397   2023.4

  7. Multi-Agent Deep-Learning Based Comparative Analysis of Team Sport Trajectories Reviewed

    Zhang Ziyi, Bunker Rory, Takeda Kazuya, Fujii Keisuke

    IEEE ACCESS   Vol. 11   page: 43305 - 43315   2023

  8. Expert-driven Rule-based Refinement of Semantic Segmentation Maps for Autonomous Vehicles

    Manibardo Eric L., Lana Ibai, Del Ser Javier, Carballo Alexander, Takeda Kazuya

    2023 IEEE INTELLIGENT VEHICLES SYMPOSIUM, IV     2023

  9. Synthesizing Realistic Snow Effects in Driving Images Using GANs and Real Data with Semantic Guidance

    Yang Hanting, Ding Ming, Carballo Alexander, Zhang Yuxiao, Ohtani Kento, Niu Yinjie, Ge Maoning, Feng Yan, Takeda Kazuya

    2023 IEEE INTELLIGENT VEHICLES SYMPOSIUM, IV     2023

  10. Open-world driving scene segmentation via multi-stage and multi-modality fusion of vision-language embedding Reviewed

    Niu Yingjie, Ding Ming, Zhang Yuxiao, Ge Maoning, Yang Hanting, Takeda Kazuya

    2023 IEEE INTELLIGENT VEHICLES SYMPOSIUM, IV     2023

  11. LiDAR Point Cloud Translation Between Snow and Clear Conditions Using Depth Images and GANs Reviewed

    Zhang Yuxiao, Ding Ming, Yang Hanting, Niu Yingjie, Feng Yan, Ge Maoning, Carballo Alexander, Takeda Kazuya

    2023 IEEE INTELLIGENT VEHICLES SYMPOSIUM, IV     2023

  12. Action Valuation of On- and Off-Ball Soccer Players Based on Multi-Agent Deep Reinforcement Learning

    Nakahara, H; Tsutsui, K; Takeda, K; Fujii, K

    IEEE ACCESS   Vol. 11   page: 131237 - 131244   2023

  13. Automatic Edge Error Judgment in Figure Skating Using 3D Pose Estimation from a Monocular Camera and IMUs

    Tanaka, R; Suzuki, T; Takeda, K; Fujii, K

    PROCEEDINGS OF THE 6TH INTERNATIONAL WORKSHOP ON MULTIMEDIA CONTENT ANALYSIS IN SPORTS, MMSPORTS 2023     page: 41 - 48   2023

  14. Learning to Predict Navigational Patterns from Partial Observations Reviewed

    Robin Karlsson, Alexander Carballo, Francisco Lepe-Salazar, Keisuke Fujii, Kento Ohtani, Kazuya Takeda

    IEEE Robotics and Automation Letters   Vol. 8 ( 9 ) page: 5592 - 5599   2023.9

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    Publishing type:Research paper (scientific journal)  

    Human beings cooperatively navigate rule-constrained environments by adhering to mutually known navigational patterns, which may be represented as directional pathways or road lanes. Inferring these navigational patterns from incompletely observed environments is required for intelligent mobile robots operating in unmapped locations. However, algorithmically defining these navigational patterns is nontrivial. This paper presents the first self-supervised learning (SSL) method for learning to infer navigational patterns in real-world environments from partial observations only. We explain how geometric data augmentation, predictive world modeling, and an information-theoretic regularizer enable our model to predict an unbiased local directional soft lane probability (DSLP) field in the limit of infinite data. We demonstrate how to infer global navigational patterns by fitting a maximum likelihood graph to the DSLP field. Experiments show that our SSL model outperforms two SOTA supervised lane graph prediction models on the nuScenes dataset. We propose our SSL method as a scalable and interpretable continual learning paradigm for navigation by perception.

    DOI: 10.1109/LRA.2023.3291924

    Web of Science

    Scopus

  15. Personalized lane changes using subjective risk-sensitive framework

    Naren Bao, Alexander Carballo, Kazuya Takeda

    Towards Human-Vehicle Harmonization     page: 211 - 222   2023.3

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    Publishing type:Part of collection (book)  

    Most of the current researches on autonomous vehicles' control assume that all vehicles should have the same patterns of driving implemented, resulting in conservative or average systems. However, these results may not be acceptable to drivers who prefer a more aggressive style of driving, while extremely cautious drivers may consider the standard outputs to be too aggressive. In this chapter, we introduce risk-sensitive control (RSC), an inverse optimal control algorithm that estimates risk-sensitive driving features and incorporate them into a receding-horizon controller. RSC uses a meta-learning algorithm to update the parameters of the cost function, continuously improving the controller online as more and more driving data is gathered from the user for subjective risk feedback. The estimator takes into account the individual differences in subjective risk analysis, in terms of driving features and surrounding vehicle locations, by adjusting the cost function and constraints. We test this approach using five-lane change scenarios, some safe and some risky, with 30 real drivers in a CARLA simulation environment. Based on both quantitative and qualitative evaluations, our experimental results demonstrate that the proposed framework can generate users' preferred driving commands during lane changes, that is, commands associated with lower subjective risk, outperforming conventional, model-based predictive control methods in terms of replicating the user's own driving behavior.

    DOI: 10.1515/9783110981223-016

    Scopus

  16. Framework for Generation and Removal of Multiple Types of Adverse Weather from Driving Scene Images Reviewed

    Hanting Yang, Alexander Carballo, Yuxiao Zhang, Kazuya Takeda

    SENSORS   Vol. 23 ( 3 ) page: 1548   2023.2

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:MDPI  

    Weather variation in the distribution of image data can cause a decline in the performance of existing visual algorithms during evaluation. Adding additional samples of target domain to training data or using pre-trained image restoration methods such as de-hazing, de-raining, and de-snowing, to improve the quality of input images are two promising solutions. In this work, we propose Multiple Weather Translation GAN (MWTG), a CycleGAN-based, dual-purpose framework that simultaneously learns weather generation and its removal from image data. MWTG consists of four GANs constrained using cycle consistency that carry out domain translation tasks between hazy, rainy, snowy, and clear weather, using an asymmetric approach. To increase network capacity, we employ a spatial feature transform (SFT) layer to fuse the features extracted from the weather layer, which contains high-level domain information from the previous generators. Further, we collect an unpaired, real-world driving dataset recorded under various weather conditions called Realistic Driving Scenes under Bad Weather (RDSBW). We qualitatively and quantitatively evaluate MWTG using the RDSBW and the variation of Cityscapes that synthesize weather effects, eg., FoggyCityscape. Our experimental results suggest that MWTG can generate realistic weather in clear images and also accurately remove noise from weather images. Furthermore, the SOTA pedestrian detector ASCP is shown to achieve an impressive gain in detection precision after image restoration using the proposed MWTG method.

    DOI: 10.3390/s23031548

    Web of Science

  17. Estimating the effect of hitting strategies in baseball using counterfactual virtual simulation with deep learning Reviewed

    Hiroshi Nakahara, Kazuya Takeda, Keisuke Fujii

    International Journal of Computer Science in Sport   Vol. 22 ( 1 ) page: 1 - 12   2023.1

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    Authorship:Corresponding author   Language:English  

    DOI: 10.2478/ijcss-2023-0001

  18. Perception and sensing for autonomous vehicles under adverse weather conditions: A survey Reviewed

    Yuxiao Zhang, Alexander Carballo, Hanting Yang, Kazuya Takeda

    ISPRS Journal of Photogrammetry and Remote Sensing   Vol. 196   page: 146 - 177   2023.1

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    Authorship:Last author, Corresponding author   Language:English  

  19. RSG-GCN: Predicting Semantic Relationships in Urban Traffic Scene With Map Geometric Prior

    Yafu Tian, Alexander Carballo, Ruifeng Li, Kazuya Takeda

    IEEE OPEN JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS   Vol. 4   page: 244 - 260   2023

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC  

    Automated identification of the relationships between traffic actors and surrounding objects, in order to describe their behavior and predict their intentions, has become the focus of increasing attention in the field of autonomous driving. Therefore, in this work, we propose a Road Scene Graphs-Graph Convolutional Network (RSG-GCN) as a novel, graph-based model for predicting the topological graph structure of a given traffic scene. The status of the actors and HD map information are integrated as prior knowledge, allowing the edges linking the actor nodes to capture potential semantic relationships, such as "vehicle approaching pedestrian" and "pedestrian waiting at intersection". To train this model, we created our own RSG dataset, as well as a relational dataset and benchmark derived from nuScenes. Our extensive range of experiments demonstrate that our model can more accurately predict semantic relationships and behavior in a given traffic scene than other popular traffic scene prediction models. In particular, regarding the use of HD map prior knowledge, we found that the resulting increase in accuracy significantly outweighs performance loss caused by the increase in graph size. The downstream applications of RSG include traffic scene retrieval and synthetic traffic scene generation, which are briefly described.

    DOI: 10.1109/OJITS.2023.3260624

    Web of Science

  20. Real-Time Graph-Based Optimization for GNSS-Doppler Integrated RTK-GNSS/IμDR Positioning System in Urban Area

    Aoki Takanose, Eijiro Takeuchi, Alexander Carballo, Junichi Meguro, Kazuya Takeda

    IEEE Intelligent Vehicles Symposium, Proceedings   Vol. 2023-June   2023

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    Publishing type:Research paper (international conference proceedings)  

    Autonomous driving of vehicles and robots requires highly accurate position information, and RTK-GNSS is expected to be utilized for this purpose. In this paper, we propose a robust and real-time operation method by introducing graph optimization into the integrated RTK-GNSS/IMU method. The proposed method is an extension of a method using vehicle trajectories that can estimate positions with lane-level accuracy even in urban areas. The position is estimated by removing GNSS multipaths from the shape of a vehicle trajectory of several hundred meters and averaging the remaining GNSS results. This method does not take into account the errors in the vehicle trajectory and cannot fully benefit from the high accuracy positioning solution of RTK-GNSS. To solve this problem, we introduce graph optimization to the base method, which treats the error state as a probabilistic model. However, general graph optimization methods have problems with processing time and outlier elimination. The proposed method solves these problems by restricting the time series data to be optimized and using a two-step optimization structure. Evaluations show that the proposed method is effective because it satisfies the requirements for real-time operation and improves accuracy compared to conventional methods.

    DOI: 10.1109/IV55152.2023.10186672

    Web of Science

    Scopus

  21. Uncertainty Aware Task Allocation for Human-Automation Cooperative Recognition in Autonomous Driving Systems

    Atsushi Kuribayashi, Eijiro Takeuchi, Alexander Carballo, Yoshio Ishiguro, Kazuya Takeda

    IEEE Intelligent Vehicles Symposium, Proceedings   Vol. 2023-June   2023

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    Publishing type:Research paper (international conference proceedings)  

    Cooperative recognition, a method to achieve human-automation cooperation in the recognition phase of the autonomous driving system, has been proposed to address the challenges in the conventional control phase cooperation, e.g., taking over vehicle control. In cooperative recognition, the operator intervenes in recognition tasks that are difficult for the automated system alone to improve driving efficiency and safety. The challenge is the integration of both human and automated systems while both participants have different characteristics, processing capabilities, and uncertainty in the decisions (recognition results). The objectives of this study are task allocation (i.e., when and for which targets the operator should intervene) taking into account the intervention efficiency and human state. And also combine the human intervention and recognition result of the automated systems to solve the uncertainties in both participants. We formulated this problem with a Partially Observable Markov Decision Process (POMDP). The simulator experiment indicated that the recognition result of the automated system and the operator's intervention were stochastically combined. The intervention requests to the operator adapted to the operator state and could be reduced while maintaining driving efficiency and minimizing risk omissions.

    DOI: 10.1109/IV55152.2023.10186725

    Web of Science

    Scopus

  22. RSG-Search: Semantic Traffic Scene Retrieval Using Graph-Based Scene Representation

    Yafu Tian, Alexander Carballo, Ruifeng Li, Kazuya Takeda

    IEEE Intelligent Vehicles Symposium, Proceedings   Vol. 2023-June   2023

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    Publishing type:Research paper (international conference proceedings)  

    Browsing specific traffic scene in large-scale dataset is an increasing demand from researchers, self-driving community and insurance companies. It is easy to search scenes with specific tags such as "rain", "snow", or "on highway". However, searching specific scene configurations, like "two vehicles waiting for a person crossing the road", is still an open problem. In this paper, we provide RSG-search, a scene-graph based traffic scene retrieval method, based on our previous research on traffic scene-graph generation. By previously translating open datasets to scene graphs, we can ignore irrelevant details, and efficiently search specific scene configuration among thousands of traffic scenes. Experiment results shows that our graph searching method is able to retrieve results for a given query with high accuracy. Our method simplifies the task of scene retrieval, opening opportunities for new applications.

    DOI: 10.1109/IV55152.2023.10186641

    Web of Science

    Scopus

  23. Predictive World Models from Real-World Partial Observations.

    Robin Karlsson, Alexander Carballo, Keisuke Fujii 0001, Kento Ohtani, Kazuya Takeda

    MOST     page: 152 - 166   2023

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    Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1109/MOST57249.2023.00024

    Other Link: https://dblp.uni-trier.de/db/conf/most/most2023.html#KarlssonC0OT23

  24. ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment Reviewed

    Robin Karlsson, Tomoki Hayashi, Keisuke Fujii, Alexander Carballo, Kento Ohtani, Kazuya Takeda

    The 33rd British Machine Vision Conference (BMVC 2022)     2022.11

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    Authorship:Last author, Corresponding author   Language:English  

    DOI: 10.48550/arXiv.2111.12460

  25. Methods of Gently Notifying Pedestrians of Approaching Objects when Listening to Music Reviewed

    Yuki Sakashita, Yoshio Ishiguro, Kento Ohtani, Kazuya TakedaTakanori Nishino,

    UIST '22: The 35th Annual ACM Symposium on User Interface Software and Technology   ( 39 ) page: 1 - 4   2022.10

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    Authorship:Corresponding author   Language:English  

    DOI: 10.1145/3526114.3558728

  26. Improvement of anomalous sound detection method considering the distribution of embedding Reviewed

    Ibuki Kuroyanagi, Tomoki Hayashi, Kazuya Takeda, Tomoki Toda

    the 24th International Congress on Acoustics     page: 5   2022.10

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    Language:English  

  27. ドライブレコーダを活用した旅の要約動画自動生成システム Reviewed

    尾頭 花奈, 石黒 祥生, 椎尾 一郎, 武田 一哉

    コンピュータ ソフトウェア   Vol. 39 ( 4 ) page: 4_144 - 4_157   2022.10

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    Authorship:Last author, Corresponding author   Language:Japanese  

    DOI: 10.11309/jssst.39.4_144

  28. Automatic Fault Detection in Race Walking From a Smartphone Camera via Fine-Tuning Pose Estimation Reviewed

    Tomohiro Suzuki, Kazuya Takeda, Keisuke Fujii

    2022 IEEE 11th Global Conference on Consumer Electronics     2022.10

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    Authorship:Corresponding author   Language:English  

    DOI: 10.1109/GCCE56475.2022.10014142

  29. Evaluation of creating scoring opportunities for teammates in soccer via trajectory prediction Reviewed

    Masakiyo Teranishi, Kazushi Tsutsui, Kazuya Takeda, Keisuke Fujii,

    9th Workshop on Machine Learning and Data Mining for Sports Analytics 2022 (MLSA'22) co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML-PKDD'22)     2022.9

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    Authorship:Corresponding author   Language:English  

    DOI: 10.48550/arXiv.2206.01899

  30. OPTIMIZATION OF AIRCRAFT FLIGHT PATHS CONSIDERING THE CONFLICTING PARAMETERS OF ECONOMY AND SAFETY Reviewed

    Tetsuya Nagashima, Ming Ding, Keisuke FUJII & Kazuya TAKEDA

    33rd Congress of the International Council of the Aeronautical Sciences     2022.9

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    Authorship:Last author, Corresponding author   Language:English  

  31. Improvement of Serial Approach to Anomalous Sound Detection by Incorporating Two Binary Cross-Entropies for Outlier Exposure Reviewed

    Ibuki Kuroyanagi, Tomoki Hayashi, Kazuya Takeda, Tomoki Toda

    the 30th European Signal Processing Conference (EUSIPCO)     2022.8

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    Language:English  

    DOI: 10.48550/arXiv.2206.05929

  32. Emergence of Collaborative Hunting via Multi-Agent Deep Reinforcement Learning Reviewed

    Kazushi Tsutsui, Kazuya Takeda, Keisuke Fujii

    International Workshop on Human Behavior Understanding (HBU'22) in conjunction with International Conference on Pattern Recognition (ICPR'22)     2022.8

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    Authorship:Corresponding author   Language:English  

  33. Evaluating a third base coach’s decision-making via game theory and machine learning Reviewed

    Hiroshi Nakahara, Kazuya Takeda, Keisuke Fujii

    MathSport International, 2022     2022.7

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    Authorship:Corresponding author   Language:English  

  34. Automatic screen-play classification in basketballvia semi-supervised learning Reviewed

    Ziyi Zhang, Kazuya Takeda, Keisuke Fujii

    Mathsport International 2022     2022.7

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    Authorship:Corresponding author   Language:English  

  35. GNSS/IMU Performance Improvement Based on Acceleration Error Estimation Using Height Variation Reviewed

    Aoki Takanose, Kaito Kondo, Yuta Hoda, Junichi Meguro, Kazuya Takeda

    15th International Symposium on Advanced Vehicle Control (AVEC’22)   Vol. Mo1B-01   2022.5

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    Authorship:Last author, Corresponding author   Language:English  

  36. SecretSign: A Method of Finding a Specific Vehicle Privately and Quickly using Flashing Lights Reviewed

    Yusuke Sakai, Hiromi Morita, Yoshio Ishiguro, Takanori Nishino, Kazuya Takeda

    IEEE Intelligent Transportation Systems Magazine   Vol. 14 ( 1 ) page: 216 - 227   2022.1

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Institute of Electrical and Electronics Engineers (IEEE)  

    DOI: 10.1109/MITS.2020.2970187

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    Scopus

  37. Data-Driven Risk-Sensitive Control for Personalized Lane Change Maneuvers

    Naren Bao, Linda Capito, Dongfang Yang, Alexander Carballo, Chiyomi Miyajima, Kazuya Takeda

    IEEE ACCESS   Vol. 10   page: 36397 - 36415   2022

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC  

    Most current research in the field of autonomous vehicle control assumes that all vehicles will follow the same patterns of automated driving behavior, resulting in systems with "conservative" or "average" driving styles. These systems may not be acceptable to drivers who prefer a more aggressive style of driving, however, while extremely cautious drivers may consider the standard outputs to be too aggressive. To address this problem, in this paper, we introduce Risk Sensitive Control (RSC), an inverse optimal control algorithm that estimates risk-sensitive driving features and incorporates them into a receding-horizon controller. RSC uses a meta-learning algorithm to update the parameters of the cost function, continuously improving the controller online as more and more driving data is gathered from the user and subjective risk feedback. An estimator takes into account individual differences in subjective risk analysis, in terms of driving features and surrounding vehicle locations, by adjusting the cost function and its constraints. We test this approach using five lane change scenarios, some safe and some risky, with thirty real drivers in a CARLA simulation environment. Our quantitative and qualitative evaluations demonstrate that the proposed framework is able to generate a user's preferred driving maneuvers during lane changes, i.e., control commands the user associates with lower subjective risk, outperforming conventional, model-based predictive control methods in terms of replicating the user's own driving behavior.

    DOI: 10.1109/ACCESS.2022.3163267

    Web of Science

  38. Real-to-Synthetic: Generating Simulator Friendly Traffic Scenes from Graph Representation

    Yafu Tian, Alexander Carballo, Ruifeng Li, Kazuya Takeda

    2022 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV)     page: 1615 - 1622   2022

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    Reproducing real-world traffic scenes in the simulator is fundamental to training self-driving systems. Creating a simulation scenario is a complex task, generally done manually: the ego-vehicle and other entities are placed and their trajectories dened, trying to recreate some situation found in real traffic. To reduce the manual burden, here we propose the Realto-Synthetic toolset. This toolset provides synthetic traffic scene in openDrive format, which can be directly simulated in many simulators such as SUMO or CARLA. Also, we provide a scene generator which generates near-realistic scene from minimum user effort. To maintain the similarity between real-world scene and generated one, here we introduce the concept "Road Scene Graph"(RSG). In this graph, nodes represent entities while edges stand for pairwise relationships. These relationships could be maintained in the scene generation process while the actor is generated according to the distribution sampled from realworld data. Experiments proved that by using "Road Scene Graph", our scene generator proposes a much more convenient way to configure traffic scenes rather than manually defining every actor's initial status and trajectories.

    DOI: 10.1109/IV51971.2022.9827441

    Web of Science

  39. An enhanced driver's risk perception modeling based on gate recurrent unit network

    Ping Peng, Ding Weiping, Liu Yongkang, Takeda Kazuya

    2022 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV)     page: 1234 - 1240   2022

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  40. Auditory and visual warning information generation of the risk object in driving scenes based on weakly supervised learning

    Niu Yinjie, Ding Ming, Zhang Yuxiao, Ohtani Kento, Takeda Kazuya

    2022 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV)     page: 1572 - 1577   2022

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  41. Deep Reinforcement Learning in a Racket Sport for Player Evaluation With Technical and Tactical Contexts.

    Ning Ding, Kazuya Takeda, Keisuke Fujii 0001

    IEEE Access   Vol. 10   page: 54764 - 54772   2022

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    Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: 10.1109/ACCESS.2022.3175314

    Web of Science

  42. Deepware: An Open-Source Toolkit for Developing and Evaluating Learning-Based and Model-Based Autonomous Driving Models

    Shunya Seiya, Alexander Carballo, Eijiro Takeuchi, Kazuya Takeda

    IEEE ACCESS   Vol. 10   page: 105734 - 105743   2022

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC  

    In recent decades, many learning-based autonomous driving systems have been proposed, and researchers have also created toolkits for developing these systems. These toolkits allow developers to train their models easily, and then test them using simulators. Existing toolkits for learning-based autonomous driving systems have some limitations however, which include inability to reuse modules or to perform accurate comparisons with model-based systems, as well as a lack of support for middle-to-middle models. As a solution, in this paper we introduce Deepware, an end-to-end toolkit for developing and evaluating learning-based autonomous driving models. Deepware includes the tools needed for collecting and evaluating datasets, training models, and evaluating models on simulators or in real-world environments using actual vehicles. Unlike existing toolkits, we used ROS as our platform, which is a set of software frameworks for robot software development widely used in autonomous driving systems as middleware, which allows cooperation with model-based systems. This approach also allows system modules to be shared when building models. In addition, it allows the comparison of learning-based and model-based methods under the same conditions. Moreover, by extracting features from model-based systems, our toolkit can also support middle-to-middle models. The proposed Deepware toolkit and dataset are available at: https://github.com/shunchan0677/deepware.

    DOI: 10.1109/ACCESS.2022.3212152

    Web of Science

  43. Disentangled Bad Weather Removal GAN for Pedestrian Detection

    Yang Hanting, Carballo Alexander, Takeda Kazuya

    2022 IEEE 95TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2022-SPRING)     2022

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  44. Driving Risk and Intervention: Subjective Risk Lane Change Dataset

    Naren Bao, Alexander Carballo, Kazuya Takeda

    2022 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV)     page: 556 - 562   2022

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    When developing truly driverless mobility for the future, one key index used to measure the matureness of a particular self-driving technology is the driver intervention rate. One method which has proven to be effective for decreasing intervention rates is the use of personalized driving models that can mimic the driving style and preferences of a targeted user, so that autonomous driving feels safer and more natural to them. To create such models, quantitative data should be collected from users in order to determine the style of driving that a particular user, or type of user, prefers. In this paper, we introduce the Subjective Risk Lane Change (SRLC) Dataset, which includes ego vehicle driving behavior data, surrounding vehicle location information, and the subjective risk scores of users, collected during both safe and risky lane change scenarios encountered in CARLA simulators, as well as demographic information for our 30 participants. Furthermore, user intervention data for all of our participants was collected from Personalized Model Predictive Controllers during the generated lane change maneuvers. As far as the authors are able to determine, no other public dataset provides driving behavior signal and intervention timing information collected during driver interventions. Our dataset can be used to gain insights into a variety of personal driving styles, allowing the improvement of adaptive autonomous driving systems, and leading to safer and more widely accepted driverless technology.

    DOI: 10.1109/IV51971.2022.9827358

    Web of Science

  45. Occlusion-Aware Motion Planning With Visibility Maximization via Active Lateral Position Adjustment

    Narksri Patiphon, Darweesh Hatem, Takeuchi Eijiro, Ninomiya Yoshiki, Takeda Kazuya

    IEEE ACCESS   Vol. 10   page: 57759 - 57782   2022

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  46. Estimating counterfactual treatment outcomes over time in multi-vehicle simulation. Reviewed

    Keisuke Fujii 0001, Koh Takeuchi, Atsushi Kuribayashi, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda

    SIGSPATIAL/GIS   ( 7 ) page: 7 - 4   2022

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:ACM  

    DOI: 10.1145/3557915.3560941

    Other Link: https://dblp.uni-trier.de/db/conf/gis/gis2022.html#0001TKTKT22

  47. Cooperative play classification in team sports via semi-supervised learning. Reviewed

    Zhang Ziyi, Kazuya Takeda, Keisuke Fujii

    International Journal of Computer Science in Sport   Vol. 21 ( 1 ) page: 111 - 121   2022

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.2478/ijcss-2022-0006

  48. Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment.

    Robin Karlsson, Tomoki Hayashi, Keisuke Fujii 0001, Alexander Carballo, Kento Ohtani, Kazuya Takeda

    BMVC     page: 699 - 699   2022

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    Publishing type:Research paper (international conference proceedings)  

    Other Link: https://dblp.uni-trier.de/rec/conf/bmvc/2022

  49. Autonomous Driving in Adverse Weather Conditions: A Survey Reviewed

    Y. Zhang, A. Carballo, H. Yang, K. Takeda

    arXiv preprint arXiv:2112.08936     2021.12

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  50. ViCE: Self-Supervised Visual Concept Embeddings as Contextual and Pixel Appearance Invariant Semantic Representations Reviewed

    Karlsson, Robin; Hayashi, Tomoki; Fujii, Keisuke; Carballo, Alexander; Ohtani, Kento; Takeda, Kazuya;

    arXiv preprint arXiv:2111.12460     2021.11

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  51. AN ENSEMBLE APPROACH TO ANOMALOUS SOUND DETECTION BASED ON CONFORMER-BASED AUTOENCODER AND BINARY CLASSIFIER INCORPORATED WITH METRIC LEARNING

    Ibuki Kuroyanagi , Tomoki Hayashi , Yusuke Adachi , Takenori Yoshimura , Kazuya Takeda , Tomoki Toda

    Proceedings of the Detection and Classification of Acoustic Scenes and Events 2021 Workshop (DCASE2021)     page: 110 - 114   2021.11

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  52. End-to-End Learning-based Driving System with Branches by Emphasizing Target Direction Reviewed

    Seiya, Shunya; Ohtani, Kento; Carballo, Alexander; Takeuchi, Eijiro; Takeda, Kazuya;

      Vol. 52 ( 6 )   2021.11

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    Authorship:Last author   Language:Japanese  

  53. FollowSelect: Path-based Menu Interaction for Intuitive Navigation Reviewed

      Vol. 62 ( 10 ) page: 1669 - 1680   2021.10

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    Authorship:Last author   Language:Japanese  

    DOI: 10.20729/00213195

  54. Flexible prediction of opponent motion with internal representation in interception behavior Reviewed

    Kazushi Tsutsui, Keisuke Fujii, Kazutoshi Kudo, Kazuya Takeda

    Biological Cybernetics   Vol. 115 ( 5 ) page: 473 - 485   2021.10

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    Authorship:Last author   Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Springer Science and Business Media LLC  

    <title>Abstract</title>Skilled interception behavior often relies on accurate predictions of external objects because of a large delay in our sensorimotor systems. To deal with the sensorimotor delay, the brain predicts future states of the target based on the current state available, but it is still debated whether internal representations acquired from prior experience are used as well. Here we estimated the predictive manner by analyzing the response behavior of a pursuer to a sudden directional change of the evasive target, providing strong evidence that prediction of target motion by the pursuer was incompatible with a linear extrapolation based solely on the current state of the target. Moreover, using neural network models, we validated that nonlinear extrapolation as estimated was computationally feasible and useful even against unknown opponents. These results support the use of internal representations in predicting target motion, suggesting the usefulness and versatility of predicting external object motion through internal representations.

    DOI: 10.1007/s00422-021-00891-9

    Web of Science

    Other Link: https://link.springer.com/article/10.1007/s00422-021-00891-9/fulltext.html

  55. Supervised sequential pattern mining of event sequences in sport to identify important patterns of play: an application to rugby union Reviewed

    Rory Bunker, Keisuke Fujii, Hiroyuki Hanada, Ichiro Takeuchi

    PLOS One     2021.9

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  56. Anomalous Sound Detection Using a Binary Classification Model and Class Centroids Reviewed

    Ibuki Kuroyanagi, Tomoki Hayashi, Kazuya Takeda , Tomoki Toda

    European Signal Processing Conference2021(EUSIPCO2021)     2021.8

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  57. Prediction of Personalized Driving Behaviors via Driver-Adaptive Deep Generative Models Reviewed

    Naren Bao, Alexander Carballo, Takeda Kazuya

    2021 IEEE Intelligent Vehicles Symposium (IV)     page: 616 - 621   2021.7

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/iv48863.2021.9575671

  58. ANOMALOUS SOUND DETECTION WITH ENSEMBLE OF AUTOENCODER AND BINARY CLASSIFICATION APPROACHES

    Ibuki Kuroyanagi , Tomoki Hayashi , Yusuke Adachi, , Takenori Yoshimura , Kazuya Takeda , Tomoki Toda

    Proceedings of the Detection and Classification of Acoustic Scenes and Events 2021 Workshop (DCASE2021)     2021.7

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  59. Leveraging state-of-the-art ASR techniques to audio captioning Reviewed

    Narisetty, Chaitanya; Hayashi, Tomoki; Ishizaki, Ryunosuke; Watanabe, Shinji; Takeda, Kazuya;

    Proceedings of the Detection and Classification of Acoustic Scenes and Events 2021 Workshop (DCASE2021)     page: 160 - 164   2021.7

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  60. Deadlock-free planner for occluded intersections using estimated visibility of hidden vehicles Reviewed

    Patiphon Narksri, Eijiro Takeuchi, Yoshiki Ninomiya, Kazuya Takeda

    Electronics (Switzerland)   Vol. 10 ( 4 ) page: 1 - 28   2021.2

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    Language:Japanese   Publishing type:Research paper (scientific journal)  

    © 2021 by the authors. Licensee MDPI, Basel, Switzerland. A common approach used for planning blind intersection crossings is to assume that hypothetical vehicles are approaching the intersection at a constant speed from the occluded areas. Such an assumption can result in a deadlock problem, causing the ego vehicle to remain stopped at an intersection indefinitely due to insufficient visibility. To solve this problem and facilitate safe, deadlock-free intersection crossing, we propose a blind intersection planner that utilizes both the ego vehicle and the approaching vehicle’s visibility. The planner uses a particle filter and our proposed visibility-dependent behavior model of approaching vehicles for predicting hidden vehicles. The behavior model is designed based on an analysis of actual driving data from multiple drivers crossing blind intersections. The proposed planner was tested in a simulation and found to be effective for allowing deadlock-free crossings at intersections where a baseline planner became stuck in a deadlock. The effects of perception accuracy and sensor position on output motion were also investigated. It was found that the proposed planner delayed crossing motion when the perception was imperfect. Furthermore, our results showed that the planner decelerated less while crossing the intersection with the front-mounted sensor configuration compared to the roof-mounted configuration due to the improved visibility. The minimum speed difference between the two sensor configurations was 1.82 m/s at an intersection with relatively poor visibility and 1.50 m/s at an intersection with good visibility.

    DOI: 10.3390/electronics10040411

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  61. Motion Analysis and Performance Improved Method for 3D LiDAR Sensor Data Compression Reviewed

    Chenxi Tu, Eijiro Takeuchi, Alexander Carballo, Chiyomi Miyajima, Kazuya Takeda

    IEEE Transactions on Intelligent Transportation Systems   Vol. 22 ( 1 ) page: 243 - 256   2021.1

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC  

    © 2000-2011 IEEE. Continuous point cloud data is being used more and more widely in practical applications such as mapping, localization and object detection in autonomous driving systems, but due to the huge volume of data involved, sharing and storing this data is currently expensive and difficult. One possible solution is the development of more efficient methods of compressing the data. Other researchers have proposed converting 3D point cloud data into 2D images, or using tree structures to store the data. In a previous study targeting streaming point cloud data, we proposed an MPEG-like compression method which utilizes simultaneous localization and mapping (SLAM) results to simulate LiDAR's operating process. In this paper, instead of imitating MPEG, we propose new strategy for more efficient reference frame distribution and more natural frame prediction, and use a different algorithm to encode the residual, greatly improving the algorithm's performance and its stability in different scenarios. We also discuss how various parameters affect compression performance. Using our proposed method, streaming point cloud data collected by LiDAR sensors can be compressed to 1/50th of its original size, with only 2 cm of Root Mean Square Error for each detected point. We evaluate our proposed method by comparing its performance with several other existing point cloud compression methods in three different driving scenarios, demonstrating that our proposed method outperforms them.

    DOI: 10.1109/TITS.2019.2956066

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  62. RSG-Net: Towards Rich Semantic Relationship Prediction for Intelligent Vehicle in Complex Environment Reviewed

    Tian, Yafu; Carballo, Alexander; Li, Ruifeng; Takeda, Kazuya;

    2021 IEEE Intelligent Vehicles Symposium (IV)     page: 546 - 552   2021

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  63. Automatic Generation of Road Trip Summary Video for Reminiscence and Entertainment using Dashcam Video Reviewed

    Kana Bito, Itiro Siio, Yoshio Ishiguro, Kazuya Takeda

    13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications     page: 181 - 190   2021

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    Language:Japanese  

    DOI: 10.1145/3409118.3475151

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  64. Learning a Model for Inferring a Spatial Road Lane Network Graph using Self-Supervision Reviewed

    Robin Karlsson, David Robert Wong, Simon Thompson, Kazuya Takeda

    The 24th IEEE International Conference on Intelligent Transportation Systems(ITSC2021)     page: 812 - 819   2021

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  65. A recognition phase Intervention Interface to Improve Naturalness of Autonomous Driving for Distracted Drivers Reviewed

    Atsushi Kuribayashi, Eijiro Takeuchi, Alexander Carballo, Yoshio Ishiguro, Kazuya Takeda

    2021 IEEE International Intelligent Transportation Systems Conference (ITSC)     page: 1737 - 1744   2021

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    Language:Japanese   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/ITSC48978.2021.9564557

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  66. Visibility Estimation in Complex, Real-World Driving Environments Using High Definition Maps Reviewed

    Patiphon Narksri, Hatem Darweesh, Eijiro Takeuchi, Yoshiki Ninomiya, Kazuya Takeda

    The 24th IEEE International Conference on Intelligent Transportation Systems(ITSC2021)     page: 2847 - 2854   2021

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  67. OpenPlanner 2.0: The Portable Open Source Planner for Autonomous Driving Applications Reviewed

    Hatem Darweesh , Eijiro Takeuchi , and Kazuya Takeda

    IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)     page: 313 - 318   2021

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  68. Characterization of Multiple 3D LiDARs for Localization and Mapping Performance using the NDT Algorithm Reviewed

    Alexander Carballo, Abraham Monrroy, David Wong, Patiphon Narksri, Jacob Lambert, Yuki Kitsukawa, Eijiro Takeuchi, Shinpei Kato, Kazuya Takeda

    2021 IEEE INTELLIGENT VEHICLES SYMPOSIUM WORKSHOPS (IV WORKSHOPS)     page: 327 - 334   2021

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    In this work, we present a detailed comparison of ten different 3D LiDAR sensors for the tasks of mapping and vehicle localization, using as common reference the Normal Distributions Transform (NDT) algorithm implemented in the self-driving open source platform Autoware. LiDAR data used in this study is a subset of our LiDAR Benchmarking and Reference (LIBRE) dataset, captured independently from each sensor, from a vehicle driven on public urban roads multiple times, at different times of the day. In this study, we analyze the performance and characteristics of each LiDAR for the tasks of (1) 3D mapping including an assessment map quality based on mean map entropy, and (2) 6-DOF localization using a ground truth reference map.

    DOI: 10.1109/IVWorkshops54471.2021.9669244

    Web of Science

  69. Eagleye: A Lane-Level Localization Using Low-Cost GNSS/IMU Reviewed

    Aoki Takanose, Yuki Kitsukawa, Junichi Megruo, Eijiro Takeuchi, Alexander Carballo, Kazuya Takeda

    2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)     page: 319 - 326   2021

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    Language:Japanese   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/IVWorkshops54471.2021.9669209

    Web of Science

  70. A Comparison of Methods for Sharing Recognition Information and Interventions to Assist Recognition in Autonomous Driving System Reviewed

    Atsushi Kuribayashi, Eijiro Takeuchi, Alexander Carballo, Yoshio Ishiguro, Kazuya Takeda

    2021 IEEE Intelligent Vehicles Symposium (IV)     page: 622 - 629   2021

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    Language:Japanese   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/IV48863.2021.9575707

    Web of Science

  71. How to monitor multiple autonomous vehicles remotely with few observers: An active management method Reviewed

    Ming Ding, Eijiro Takeuchi, Yoshio Ishiguro, Yoshiki Ninomiya, Nobuo Kawaguchi and Kazuya Takeda

    2021 IEEE Intelligent Vehicles Symposium (IV)     page: 1168 - 1173   2021

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  72. Anomalous Sound Detection Using a Binary Classification Model and Class Centroids

    Kuroyanagi Ibuki, Hayashi Tomoki, Takeda Kazuya, Toda Tomoki

    29TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO 2021)     page: 1995 - 1999   2021

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    Language:Japanese  

    Web of Science

  73. A Method for Location Initialization of Handheld Devices using Autonomous Driving Vehicles for Interactive Systems

    Ishiguro Yoshio, Takeda Kazuya

    AUTOMOTIVEUI '21 ADJUNCT PROCEEDINGS: 13TH INTERNATIONAL ACM CONFERENCE ON AUTOMOTIVE USER INTERFACES AND INTERACTIVE VEHICULAR APPLICATIONS     page: 102 - 106   2021

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    Language:Japanese  

    DOI: 10.1145/3473682.3480273

    Web of Science

  74. Cross-Lingual Voice Conversion using a Cyclic Variational Auto-encoder and a WaveNet Vocoder Reviewed

    Hikaru Nakatani, Patrick Lumban Tobing, Kazuya Takeda, Tomoki Toda

    2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings     page: 520 - 526   2020.12

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    Publishing type:Research paper (international conference proceedings)  

    © 2020 APSIPA. We propose a novel, cross-lingual voice conversion (VC) method using a cyclic variational auto-encoder (CycleVAE). Voice conversion is the transformation of the voice of one speaker into the voice of another speaker, while cross-lingual VC performs voice conversion between speakers who speak different languages. When using VC methods based on parallel learning, it is necessary to prepare accented speech uttered by the source or target speaker, using the pronunciation system of the speaker's mother tongue. On the other hand, VC methods which use a non-parallel learning approach can utilize the natural speech data of both the source and target speakers, produced in their own native languages. It then becomes necessary, however, to deal with the issues of time-alignment and language mismatches. To address these issues, we apply CycleVAE to cross-lingual VC as a sophisticated, non-parallel method of VC. We also apply the WaveNet vocoder in the waveform generation process of CycleVAE-VC to improve overall conversion quality. Our objective and subjective experimental results when performing cross-lingual VC from a native English speaker to a native Japanese speaker confirm that the proposed method achieves a higher level of naturalness and speaker similarity than a conventional RNN-based parallel VC method using accented speech.

    Scopus

    Other Link: https://dblp.uni-trier.de/conf/apsipa/2020

  75. Generation of Origami Folding Animations from 3D Point Cloud Using Latent Space Interpolation Reviewed

    Chiaki Nakagaito, Takanori Nishino, Kazuya Takeda

    SIGGRAPH Asia 2020 Posters. SA 2020     page: 30 - 2   2020.12

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    Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1145/3415264.3425450

    Scopus

    Other Link: https://dblp.uni-trier.de/db/conf/siggrapha/siggrapha2020posters.html#NakagaitoNT20

  76. Road Scene Graph: A Semantic Graph-Based Scene Representation Dataset for Intelligent Vehicles Reviewed

    Yafu Tian, Alexander Carballo, Ruifeng Li, Kazuya Takeda

    CoRR   Vol. abs/2011.13588   2020.11

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    Publishing type:Research paper (scientific journal)  

    Rich semantic information extraction plays a vital role on next-generation
    intelligent vehicles. Currently there is great amount of research focusing on
    fundamental applications such as 6D pose detection, road scene semantic
    segmentation, etc. And this provides us a great opportunity to think about how
    shall these data be organized and exploited.
    In this paper we propose road scene graph,a special scene-graph for
    intelligent vehicles. Different to classical data representation, this graph
    provides not only object proposals but also their pair-wise relationships. By
    organizing them in a topological graph, these data are explainable,
    fully-connected, and could be easily processed by GCNs (Graph Convolutional
    Networks). Here we apply scene graph on roads using our Road Scene Graph
    dataset, including the basic graph prediction model. This work also includes
    experimental evaluations using the proposed model.

    arXiv

    Other Link: http://arxiv.org/pdf/2011.13588v1

  77. CONFORMER-BASED SOUND EVENT DETECTION WITH SEMI-SUPERVISED LEARNING AND DATA AUGMENTATION Reviewed

    Koichi Miyazaki, Tatsuya Komatsu, Tomoki Hayashi, Shinji Watanabe, Tomoki Toda, Kazuya Takeda

    Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE Workshop)     page: 100 - 104   2020.11

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    Authorship:Last author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

  78. Point Grid Map-Based Mid-To-Mid Driving without Object Detection Reviewed

    Shunya Seiya, Alexander Carballo, Eijiro Takeuchi, and Kazuya Takeda

    2020 IEEE Intelligent Vehicles Symposium(IV)     2020.10

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    Authorship:Last author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1109 / IV47402.2020.9304809

  79. Trajectory prediction with imitation learning reflecting defensive evaluation in team sports Reviewed

    Masakiyo Teranishi, Keisuke Fujii, Kazuya Takeda

    2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020     page: 124 - 125   2020.10

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    Publishing type:Research paper (international conference proceedings)  

    © 2020 IEEE. In team sports, qualitative video analysis is mainly used for decision making of team tactics because of the complex interaction. Among the quantitative analyses, most of studies in team trajectory generation have been evaluated only on prediction errors and did not take tactical evaluations (e.g., good defense) into consideration. In this paper, we propose a trajectory prediction method incorporating the defensive evaluation (i.e., how well they protect the goal) into multi-agent imitation learning model. Although the proposed method had the similar prediction performance to the existing method, our method generated an improved trajectory in terms of defensive evaluation.

    DOI: 10.1109/GCCE50665.2020.9291841

    Scopus

    Other Link: https://dblp.uni-trier.de/db/conf/gcce/gcce2020.html#TeranishiFT20

  80. Extracting Human-Like Driving Behaviors from Expert Driver Data Using Deep Learning Reviewed

    Kyle Sama, Yoichi Morales, Hailong Liu, Naoki Akai, Alexander Carballo, Eijiro Takeuchi, Kazuya Takeda

    IEEE Transactions on Vehicular Technology   Vol. 69 ( 9 ) page: 9315 - 9329   2020.9

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC  

    © 1967-2012 IEEE. This paper introduces a method to extract driving behaviors from a human expert driver which are applied to an autonomous agent to reproduce proactive driving behaviors. Deep learning techniques were used to extract latent features from the collected data. Extracted features were clustered into behaviors and used to create velocity profiles allowing an autonomous driving agent could drive in a human-like manner. By using proactive driving behaviors, the agent could limit potential sources of discomfort such as jerk and uncomfortable velocities. Additionally, we proposed a method to compare trajectories where not only the geometric similarity is considered, but also velocity, acceleration and jerk. Experimental results in a simulator implemented in ROS show that the autonomous agent built with the driving behaviors was capable of driving similarly to expert human drivers.

    DOI: 10.1109/TVT.2020.2980197

    Web of Science

    Scopus

  81. Policy learning with partial observation and mechanical constraints for multi-person modeling Reviewed

    Keisuke Fujii, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda

    CoRR   Vol. abs/2007.03155   2020.7

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    Publishing type:Research paper (scientific journal)  

    Extracting the rules of real-world biological multi-agent behaviors is a
    current challenge in various scientific and engineering fields. Biological
    agents generally have limited observation and mechanical constraints; however,
    most of the conventional data-driven models ignore such assumptions, resulting
    in lack of biological plausibility and model interpretability for behavioral
    analyses in biological and cognitive science. Here we propose sequential
    generative models with partial observation and mechanical constraints, which
    can visualize whose information the agents utilize and can generate
    biologically plausible actions. We formulate this as a decentralized
    multi-agent imitation learning problem, leveraging binary partial observation
    models with a Gumbel-Softmax reparameterization and policy models based on
    hierarchical variational recurrent neural networks with physical and
    biomechanical constraints. We investigate the empirical performances using
    real-world multi-person motion datasets from basketball and soccer games.

    arXiv

    Other Link: http://arxiv.org/pdf/2007.03155v1

  82. Personalized Subjective Driving Risk: Analysis and Prediction Reviewed

    Bao Naren, Carballo Alexander, Miyajima Chiyomi, Takeuchi Eijiro, Takeda Kazuya

    JOURNAL OF ROBOTICS AND MECHATRONICS   Vol. 32 ( 3 ) page: 503-519   2020.6

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    Web of Science

  83. Convolution augmented transformer for semi-supervised sound event detection Reviewed

    K Miyazaki, T Komatsu, T Hayashi, S Watanabe, T Toda, K Takeda

    Proc. Workshop Detection Classification Acoust. Scenes Events (DCASE)     page: 100 - 104   2020.6

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    Authorship:Last author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

  84. Weakly-Supervised Sound Event Detection with Self-Attention Reviewed

    Koichi Miyazaki, Tatsuya Komatsu, Tomoki Hayashi, Shinji Watanabe, Tomoki Toda, Kazuya Takeda

    ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings   Vol. 2020-May   page: 66 - 70   2020.5

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    © 2020 IEEE. In this paper, we propose a novel sound event detection (SED) method that incorporates a self-attention mechanism of the Transformer for a weakly-supervised learning scenario. The proposed method utilizes the Transformer encoder, which consists of multiple self-attention modules, allowing to take both local and global context information of the input feature sequence into account. Furthermore, inspired by the great success of BERT in the natural language processing field, the proposed method introduces a special tag token into the input sequence for weak label prediction, which enables the aggregation of the whole sequence information. To demonstrate the performance of the proposed method, we conduct the experimental evaluation using the DCASE2019 Task4 dataset. The experimental results demonstrate that the proposed method outperforms the DCASE2019 Task4 baseline method, which is based on the convolutional recurrent neural network, and the self-attention mechanism effectively works for SED.

    DOI: 10.1109/ICASSP40776.2020.9053609

    Scopus

    Other Link: https://dblp.uni-trier.de/db/conf/icassp/icassp2020.html#MiyazakiKH0TT20

  85. Characterization of Multiple 3D LiDARs for Localization and Mapping using Normal Distributions Transform Reviewed

    Alexander Carballo, Abraham Monrroy, David Wong, Patiphon Narksri, Jacob Lambert, Yuki Kitsukawa, Eijiro Takeuchi, Shinpei Kato, Kazuya Takeda

    arXiv preprint arXiv:2004.01374     page: -   2020.4

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  86. LIBRE: The multiple 3d lidar dataset Reviewed

    Alexander Carballo, Jacob Lambert, Abraham Monrroy, David Wong, Patiphon Narksri, Yuki Kitsukawa, Eijiro Takeuchi, Shinpei Kato, Kazuya Takeda

    arXiv preprint arXiv:2003.06129     page: -   2020.3

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  87. A Survey of Autonomous Driving: Common Practices and Emerging Technologies Reviewed

    Ekim Yurtsever, Jacob Lambert, Alexander Carballo, Kazuya Takeda

    IEEE Access   Vol. 8   page: 58443 - 58469   2020

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC  

    © 2013 IEEE. Automated driving systems (ADSs) promise a safe, comfortable and efficient driving experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The full potential of ADSs cannot be realized unless the robustness of state-of-the-art is improved further. This paper discusses unsolved problems and surveys the technical aspect of automated driving. Studies regarding present challenges, high-level system architectures, emerging methodologies and core functions including localization, mapping, perception, planning, and human machine interfaces, were thoroughly reviewed. Furthermore, many state-of-the-art algorithms were implemented and compared on our own platform in a real-world driving setting. The paper concludes with an overview of available datasets and tools for ADS development.

    DOI: 10.1109/ACCESS.2020.2983149

    Web of Science

    Scopus

    arXiv

    Other Link: http://arxiv.org/pdf/1906.05113v3

  88. Performance Analysis of 10 Models of 3D LiDARs for Automated Driving Reviewed

    Jacob Lambert, Alexander Carballo, Abraham Monrroy Cano, Patiphon Narksri, David Wong, Eijiro Takeuchi, Kazuya Takeda

    IEEE Access   Vol. 8   page: 131699 - 131722   2020

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    Language:Japanese   Publishing type:Research paper (scientific journal)  

    © 2013 IEEE. Automated vehicle technology has recently become reliant on 3D LiDAR sensing for perception tasks such as mapping, localization and object detection. This has led to a rapid growth in the LiDAR manufacturing industry with several competing makers releasing new sensors regularly. With this increased variety of LiDARs, each with different properties such as number of laser emitters, resolution, field-of-view, and price tags, a more in-depth comparison of their characteristics and performance is required. This work compares 10 commonly used 3D LiDARs, establishing several metrics to assess their performance. Various outstanding issues with specific LiDARs were qualitatively identified. The accuracy and precision of individual LiDAR beams and accumulated point clouds are evaluated in a controlled environment at distances from 5 to 180 meters. Reflective targets were used to characterize intensity patterns and quantify the impact of surface reflectivity on accuracy and precision. A vehicle and pedestrian mannequin were also used as additional targets of interest. A thorough assessment of these LiDARs is given with their potential applicability for automated driving tasks. The data collected in these experiments and analysis tools are all shared openly.

    DOI: 10.1109/ACCESS.2020.3009680

    Web of Science

    Scopus

  89. END-TO-END AUTOMATIC SPEECH RECOGNITION INTEGRATED WITH CTC-BASED VOICE ACTIVITY DETECTION Reviewed

    Yoshimura Takenori, Hayashi Tomoki, Takeda Kazuya, Watanabe Shinji

    2020 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING     page: 6999 - 7003   2020

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  90. Intelligibility enhancement based on speech waveform modification using hearing impairment Reviewed

    Shu Hikosaka, Shogo Seki, Tomoki Hayashi, Kazuhiro Kobayashi, Kazuya Takeda, Hideki Banno, Tomoki Toda

    Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH   Vol. 2020-October   page: 4059 - 4063   2020

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    Publishing type:Research paper (international conference proceedings)  

    Copyright © 2020 ISCA In this paper, we propose a speech waveform modification method which incorporates a hearing impairment simulator, to improve speech intelligibility for the hearing-impaired. The settings of hearing aid devices usually need to be manually adjusted to suit the needs of each user, which creates a significant burden. To address this issue, the proposed method creates a spectral shaping filter, using a hearing impairment simulator capable of estimating speech signals as perceived by a specific hearing-impaired person. We conduct objective and subjective evaluations through simulations using the hearing impairment simulator. Our experimental results demonstrate that; 1) the proposed spectral shaping filter can significantly improve both speech intelligibility and quality, 2) the filter can be combined with a well-known speech intelligibility enhancement technique based on power compensation using dynamic range compression (DRC), and 3) speech intelligibility can be further improved by controlling the trade-off between filtering and DRC-based power compensation.

    DOI: 10.21437/Interspeech.2020-2062

    Scopus

    Other Link: https://dblp.uni-trier.de/db/conf/interspeech/interspeech2020.html#HikosakaSHKTBT20

  91. Point Grid Map-Based Mid-To-Mid Driving without Object Detection Reviewed

    Shunya Seiya, Alexander Carballo, Eijiro Takeuchi, Kazuya Takeda

    IEEE Intelligent Vehicles Symposium, Proceedings     page: 2044 - 2051   2020

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    Publishing type:Research paper (international conference proceedings)  

    © 2020 IEEE. Teaching autonomous vehicles to imitate human driving in complex, urban traffic scenarios is a difficult task. 'End-to-end' autonomous driving systems, based on 'imitation learning', are an expecting approach. A model learns the relationships between sensing input and vehicle control signal outputs. These methods can successfully achieve driving in simple scenarios such as lane keeping. In contrast, the 'mid-to-mid' autonomous driving methods now being proposed. In such framework, the model learns the relationships between pre-processed feature maps from the model-based system as input and the future position of the ego vehicle as the output. Mid-to-mid driving methods can direct vehicles more robustly than end-to-end driving methods in some complex driving environments. However, mid-to-mid driving methods use the results of the object detection module to create the feature map. If object detection fails, or detection performance is poor due to changes in the driving environment, prediction performance may also be degraded. Our proposed method uses a prediction module that outputs point grid maps directly, without the use of an object detection module, which are then incorporated into the feature map. Point grid maps represent the locations of surrounding vehicles and obstacles directly, based on LiDAR point cloud data. Since the results of object detection are not used by the prediction module, detection performance does not affect prediction performance. In this study we conduct two experiments, an off-line evaluation using a Lyft dataset, and an on-line evaluation using the CARLA simulator. The results show that our model can achieve the same level of ego-vehicle position prediction performance as a model using annotated object location information.

    DOI: 10.1109/IV47402.2020.9304809

    Scopus

    Other Link: https://dblp.uni-trier.de/db/conf/ivs/ivs2020.html#SeiyaCTT20

  92. Nagoya University at TRECVID 2014: The instance search task Reviewed

    Cai Zhi Zhu, Yinqiang Zheng, Ichiro Ide, Shinichi Satoh, Kazuya Takeda

    2014 TREC Video Retrieval Evaluation, TRECVID 2014     2020

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    © 2020 2014 TREC Video Retrieval Evaluation. All rights reserved. This paper presents our recent progress on a video object retrieval system that participated in the Instance Search (INS) task of the TRECVID 2014. Basically the system is a further extension of our previous Bag-of-Words (BOW) framework, with emphasis on pursuing a practical spatial re-ranking method scalable to large video database this year. We take the asymmetrical dissimilarities based system, which performed best in the INS2013 task, as the baseline, and re-rank with an improved spatial verification method. Experiments carried out the TRECVID INS2013 and INS2014 consistently show that, our re-ranking algorithm is able to further improve the baseline system at a rather fast speed.

    Scopus

  93. Intervention Force-based Imitation Learning for Autonomous Navigation in Dynamic Environments. Reviewed

    Tomoya Yokoyama, Shunya Seiya, Eijiro Takeuchi, Kazuya Takeda

        page: 1679 - 1688   2020

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    Publishing type:Research paper (international conference proceedings)  

    Other Link: https://dblp.uni-trier.de/conf/apsipa/2020

  94. Attention-Based Speech Recognition Using Gaze Information

    Osamu Segawa, Tomoki Hayashi, Kazuya Takeda

    2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)     page: 465-470   2019.12

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  95. ITS+DM Hackathon (ITSC 2017): Lane Departure Prediction with Naturalistic Driving Data Reviewed

    Andrey Alekseenko, Hien Q. Dang, Gaurav Bansal, Javier Sanchez-Medina, Chiyomi Miyajima, Takatsugu Hirayama, Kazuya Takeda, Ichiro Ide

    IEEE Intelligent Transportation Systems Magazine   Vol. 11 ( 4 ) page: 78 - 93   2019.12

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    © 2009-2012 IEEE. On October 16th, 2017, in Yokohama, Japan, from 8:00 to 18:00, the first Intelligent Transportation Systems plus Data Mining challenge was organized under the umbrella of the 2017 IEEE Intelligent Transportation Systems Conference, the flagship conference of the IEEE Intelligent Transportation Systems Society. This activity was organized thanks to a three way collaboration between the ITS Society, Nagoya University, and the IEEE ITSC 2017 organizers. The twenty-three contestants, coming from eleven different countries, faced a classic Naturalistic Driving problem: Lane Departure detection. This paper presents the three best solutions produced. The solutions submitted by most of the participants were very diverse and interesting, but overall, the top ones concurred in the use of ensemble learning after a very interesting feature engineering phase. This hackathon formulation was complex in several ways. It was complex in terms of class imbalance, the challenge time duration and the fact that the provided dataset included only numerical measurements coming from the inertial unit in the testing car. That restriction made it difficult to expect outstanding results ? the best one was only slightly over 3% above baseline. However, the organizers thought that such complexities pushed participants to show their repertoire as data scientists, taking into consideration for example computer power load of the different algorithms tested, and overall yielding more interesting approaches to share with the community. Additionally, the most interesting learned lessons were shared, from both an organizational and technical point of view.

    DOI: 10.1109/MITS.2018.2880264

    Web of Science

    Scopus

  96. Motion Analysis and Performance Improved Method for 3D LiDAR Sensor Data Compression

    Chenxi Tu,Eijiro Takeuchi,Alexander Carballo,Chiyomi Miyajima,Kazuya Takeda

    IEEE transction on ITS     page: -   2019.11

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  97. Underdetermined Source Separation Based on Generalized Multichannel Variational Autoencoder Reviewed

    Shogo Seki, Hirokazu Kameoka, Li Li, Tomoki Toda, and Kazuya Takeda

    IEEE access     page: -   2019.11

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  98. Estimating the Probabilities of Surrounding Vehicles' Intentions and Trajectories using a Behavior Planner

    Hatem Darweesh, Eijiro Takeuchi, Kazuya Takeda

    International journal of automotive engineering   Vol. 10 ( 4 ) page: 299-308   2019.11

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  99. ESPnet-TTS: Unified, Reproducible, and Integratable Open Source End-to-End Text-to-Speech Toolkit Reviewed

    Tomoki Hayashi, Ryuichi Yamamoto, Katsuki Inoue, Takenori Yoshimura, Shinji Watanabe, Tomoki Toda, Kazuya Takeda, Yu Zhang, Xu Tan

    arXiv preprint arXiv:1910.10909     page: 00   2019.10

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  100. Effects on user perception of a'modified'speed experience through in-vehicle virtual reality Reviewed

    Yusuke Sakai, Toshimitsu Watanabe, Yoshio Ishiguro, Takanori Nishino, Kazuya Takeda

    Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications: Adjunct Proceedings     page: 166-170   2019.9

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  101. LeadingDisplay: a versatile, robotic display for infotainment in autonomous vehicles Reviewed

    Yoshio Ishiguro, Kazuya Takeda

    Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications: Adjunct Proceedings     page: 405-409   2019.9

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  102. Improving target selection accuracy for vehicle touch screens Reviewed

    Kosuke Ito, Kento Ohtani, Yoshio Ishiguro, Takanori Nishino, Kazuya Takeda

    Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications: Adjunct Proceedings     page: 176-180   2019.9

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  103. Robustness of Statistical Voice Conversion Based on Direct Waveform Modification Against Background Sounds Reviewed

    Yusuke Kurita, Kazuhiro Kobayashi, Kazuya Takeda, Tomoki Toda

    Proc. Interspeech 2019     page: 684-688   2019.9

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  104. Pre-Trained Text Embeddings for Enhanced Text-to-Speech Synthesis Reviewed

    Tomoki Hayashi, Shinji Watanabe, Tomoki Toda, Kazuya Takeda, Shubham Toshniwal, Karen Livescu

    Proc. Interspeech 2019     page: 4430-4434   2019.9

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  105. Effects on the Perception of Speed and Normality When Virtual Reality Scenes Reviewed

    Yusuke Sakai, Toshimitsu Watanabe, Yoshio Ishiguro, Takanori Nishino, Kazuya Takeda

    11th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications (2019 Automotive User Interfaces)     2019.9

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  106. Real-time Streaming Point Cloud Compression for 3D LiDAR Sensor Using U-net

    Chenxi Tu,Eijiro Takeuchi,Alexander Carballo,Kazuya Takeda

    IEEE access     page: -   2019.8

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  107. Overview of the five key research groups within the Behaviour Signal Processing Laboratory (Takeda Laboratory) at Nagoya University

    Kazuya Takeda

    Impact   Vol. 2019 ( 5 ) page: 32-35   2019.6

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  108. A Survey of Autonomous Driving: Common Practices and Emerging Technologies Reviewed

    Ekim Yurtsever, Jacob Lambert, Alexander Carballo, Kazuya Takeda

    arXiv preprint arXiv:1906.05113     page: 00   2019.6

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  109. Risky action recognition in lane change video clips using deep spatiotemporal networks with segmentation mask transfer Reviewed

    Ekim Yurtsever, Yongkang Liu, Jacob Lambert, Chiyomi Miyajima, Eijiro Takeuchi, Kazuya Takeda, John HL Hansen

    arXiv     page: 1906.02859   2019.6

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  110. A Predictive Reward Function for Human-Like Driving Based on a Transition Model of Surrounding Environment Reviewed

    Daiki Hayashi, Yunfei Xu, Takashi Bando, Kazuya Takeda

    2019 International Conference on Robotics and Automation (ICRA)     page: 7618-7624   2019.5

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  111. Point cloud compression for 3D LiDAR sensor using recurrent neural network with residual blocks Reviewed

    Chenxi Tu, Eijiro Takeuchi, Alexander Carballo, Kazuya Takeda

    2019 International Conference on Robotics and Automation (ICRA)     page: 3274-3280   2019.5

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  112. SCENE-DEPENDENT ANOMALOUS ACOUSTIC-EVENT DETECTION BASED ON CONDITIONAL WAVENET AND I-VECTOR

    Komatsu Tatsuya, Hayashi Tomoki, Kondo Reishi, Toda Tomoki, Takeda Kazuya

    2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)     page: 870-874   2019.5

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  113. Point Cloud Compression for 3D LiDAR Sensor using Recurrent Neural Network with Residual Blocks

    Tu Chenxi, Takeuchi Eijiro, Carballo Alexander, Takeda Kazuya

    2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)     page: 3274-3280   2019.5

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  114. A Predictive Reward Function for Human-like Driving based on a Transition Model of Surrounding Environment

    Hayashi Daiki, Xu Yunfei, Bando Takashi, Takeda Kazuya

    2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)     page: 7618-7624   2019.5

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  115. An Empirical Study of Adaptive Training of Daily Activity Classifier and Chat Application Designed for the Elderly to Go Out Reviewed

    Akira Tamamori, Yoshio Ishiguro, Kei Hiroi, Nobuo Kawaguchi, Kazuya Takeda

    IPSJ Transactions on Consumer Device & Systems (CDS)   Vol. 9 ( 2 ) page: 33 - 46   2019.5

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  116. Environmental sound processing and its applications Reviewed

    Koichi Miyazaki, Tomoki Toda, Tomoki Hayashi, Kazuya Takeda

    IEEJ Transactions on Electrical and Electronic Engineering   Vol. 14 ( 3 ) page: 340 - 351   2019.3

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    © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. As part of the effort to develop techniques for understanding environments using sound, many studies in the field of computational auditory scene analysis have focused on using computers to perform functions carried out naturally by the human auditory system. Thanks to recent progress in machine-learning techniques, these environmental sound-processing techniques have significantly improved and a widening variety of applications has resulted in considerable interest in this field. In this review, we introduce the fundamental techniques of environmental sound processing, as well as recent advances in front-end and back-end processing and potential applications for these techniques. Prospects for further progress in the field of environmental sound processing and the challenges still to be overcome are also discussed. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

    DOI: 10.1002/tee.22868

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  117. A traffic flow simulation framework for learning driver heterogeneity from naturalistic driving data using autoencoders Reviewed

    Ekim Yurtsever, Chiyomi Miyajima, Kazuya Takeda

    International Journal of Automotive Engineering   Vol. 10 ( 1 ) page: 86-93   2019.3

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  118. Real-Time Streaming Point Cloud Compression for 3D LiDAR Sensor Using U-Net

    Tu Chenxi, Takeuchi Eijiro, Carballo Alexander, Takeda Kazuya

    IEEE ACCESS   Vol. 7   page: 113616-113625   2019

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    DOI: 10.1109/ACCESS.2019.2935253

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  119. Impact of driver behavior on fuel consumption: Classification, evaluation and prediction using machine learning Reviewed

    Peng Ping, Wenhu Qin, Yang Xu, Chiyomi Miyajima, Kazuya Takeda

    IEEE Access   Vol. 7   page: 78515 - 78532   2019

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    © 2013 IEEE. Driving behavior has a large impact on vehicle fuel consumption. Dedicated study on the relationship between the driving behavior and fuel consumption can contribute to decreasing the energy cost of transportation and the development of the behavior assessment technology for the ADAS system. Therefore, it is vital to evaluate this relationship in order to develop more ecological driving assistance systems and improve the vehicle fuel economy. However, modeling driving behavior under the dynamic driving conditions is complex, making a quantitative analysis of the relationship between the driving behavior and the fuel consumption difficult. In this paper, we introduce two kinds of machine learning methods for evaluating the fuel efficiency of driving behavior using the naturalistic driving data. In the first stage, we use an unsupervised spectral clustering algorithm to study the macroscopic relationship between driving behavior and fuel consumption, using the data collected during the natural driving process. In the second stage, the dynamic information from the driving environment and natural driving data is integrated to generate a model of the relationship between various driving behaviors and the corresponding fuel consumption features. The dynamic environment factors are coded into a processable, digital form using a deep learning-based object detection method so that the environmental data can be linked with the vehicle's operating signal data to provide the training data for the deep learning network. The training data are labeled according to its fuel consumption feature distribution, which is obtained from the road segment data and historical driving data. This deep learning-based model can then be used as a predictor of the fuel consumption associated with different driving behaviors. Our results show that the proposed method can effectively identify the relationship between the driving behavior and the fuel consumption on both macro and micro levels, allowing for end-to-end fuel consumption feature prediction, which can then be applied in the advanced driving assistance systems.

    DOI: 10.1109/ACCESS.2019.2920489

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  120. Training Engineers in Autonomous Driving Technologies using Autoware

    Carballo Alexander, Wong David, Ninomiya Yoshiki, Kato Shinpei, Takeda Kazuya

    2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC)     page: 3347-3354   2019

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  121. Risky Action Recognition in Lane Change Video Clips using Deep Spatiotemporal Networks with Segmentation Mask Transfer

    Yurtsever Ekim, Liu Yongkang, Lambert Jacob, Miyajima Chiyomi, Takeuchi Eijiro, Takeda Kazuya, Hansen John H. L.

    2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC)     page: 3100-3107   2019

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  122. Personalized Safety-focused Control by Minimizing Subjective Risk

    Bao Naren, Yang Dongfang, Carballo Alexander, Ozguner Umit, Takeda Kazuya

    2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC)     page: 3853-3858   2019

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  123. Crossing Blind Intersections from a Full Stop Using Estimated Visibility of Approaching Vehicles

    Narksri Patiphon, Takeuchi Eijiro, Ninomiya Yoshiki, Takeda Kazuya

    2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC)     page: 2427-2434   2019

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  124. ATTENTION-BASED SPEECH RECOGNITION USING GAZE INFORMATION

    Segawa Osamu, Hayashi Tomoki, Takeda Kazuya

    2019 IEEE AUTOMATIC SPEECH RECOGNITION AND UNDERSTANDING WORKSHOP (ASRU 2019)     page: 465-470   2019

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  125. Optimizing Learned Object Detection on Point Clouds from 3D Lidars Through Range and Sparsity Information

    Lambert Jacob, Takeuchi Eijiro, Takeda Kazuya

    2019 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC)     page: 407-413   2019

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  126. Daily activity recognition based on recurrent neural network using multi-modal signals Reviewed

    Akira Tamamori, Tomoki Hayashi, Tomoki Toda, Kazuya Takeda

    APSIPA Transactions on Signal and Information Processing   Vol. 7 ( e21 ) page: 1 - 11   2018.12

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    Copyright © 2018 The Authors. Our aim is to develop a smartphone-based life-logging system. Human activity recognition (HAR) is one of the core techniques to realize it. Recent studies reported the effectiveness of feed-forward neural network (FF-NN) and recurrent neural network (RNN) as a classifier for HAR task. However, there are still unresolved problems in those studies: (1) a life-logging system using only a smartphone for recording device has not been developed, (2) only indoor activities have been utilized for evaluation, (3) insufficient investigations/evaluations of RNN. In this study, we address these unresolved problems as follows: (1) we build a prototype system for life-logging and conduct data recording experiment on this system to include both indoor and outdoor activities. The experimental results of HAR on this new dataset showed that RNN-based classifier was still effective. (2) From the results of a HAR experiment, it was demonstrated that a multi-layered Simple Recurrent Unit with a non-linear transform at the bottom layer and a highway-connection was the most effective. (3) We could grasp the reason for the improvement of RNN from FF-NN by observing the posterior probabilities over test data.

    DOI: 10.1017/ATSIP.2018.25

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  127. BACK-TRANSLATION-STYLE DATA AUGMENTATION FOR END-TO-END ASR Reviewed

    Hayashi Tomoki, Watanabe Shinji, Zhang Yu, Toda Tomoki, Hori Takaaki, Astudillo Ramon, Takeda Kazuya

    2018 IEEE WORKSHOP ON SPOKEN LANGUAGE TECHNOLOGY (SLT 2018)     page: 426-433   2018.12

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  128. Back-translation-style data augmentation for end-to-end ASR

    Tomoki Hayashi, Shinji Watanabe, Yu Zhang, Tomoki Toda, Takaaki Hori, Ramon Astudillo, Kazuya Takeda

    2018 IEEE Spoken Language Technology Workshop (SLT)     page: 426-433   2018.12

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  129. End-to-End Navigation with Branch Turning Support using Convolutional Neural Network

    Seiya Shunya, Carballo Alexander, Takeuchi Eijiro, Miyajima Chiyomi, Takeda Kazuya

    2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO)     page: 499-506   2018.12

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  130. ITS+ DM Hackathon (ITSC 2017): Lane departure prediction with naturalistic driving data

    Andrey Alekseenko, Hien Q Dang, Gaurav Bansal, Javier J Sánchez-Medina, Chiyomi Miyajima, Takatsugu Hirayama, Kazuya Takeda, Ichiro Ide

    IEEE Intelligent Transportation Systems Magazine     page: 00   2018.11

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  131. Driving Feature Extraction and Behavior Classification Using an Autoencoder to Reproduce the Velocity Styles of Experts Reviewed

    Sama Kyle, Morales Yoichi, Akai Naoki, Liu Hailong, Takeuchi Eijiro, Takeda Kazuya

    2018 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC)     page: 1337-1343   2018.11

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  132. SecretSign: A Method of Finding an Off-line Target Object without Revealing the Target to Observers

    Sakai Yusuke, Morita Hiromi, Ishiguro Yoshio, Nishino Takanori, Takeda Kazuya

    2018 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC)     page: 3651-3656   2018.11

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  133. High Density Ground Maps using Low Boundary Height Estimation for Autonomous Vehicles Reviewed

    Carballo Alexander, Takeuchi Eijiro, Takeda Kazuya

    2018 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC)     page: 3811-3818   2018.11

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  134. SecretSign: A Method of Finding an Off-Line Target Object without Revealing the Target to Observers

    Yusuke Sakai, Hiromi Morita, Yoshio Ishiguro, Takanori Nishino, Kazuya Takeda

    2018 21st International Conference on Intelligent Transportation Systems (ITSC)     page: 3651-3656   2018.11

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  135. Generalized multichannel variational autoencoder for underdetermined source separation

    Shogo Seki, Hirokazu Kameoka, Li Li, Tomoki Toda, Kazuya Takeda

    arXiv preprint arXiv:1810.00223     page: 00   2018.9

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  136. Connectionist Temporal Classification-based Sound Event Encoder for Converting Sound Events into Onomatopoeic Representations

    Miyazaki Koichi, Hayashi Tomoki, Toda Tomoki, Takeda Kazuya

    2018 26TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO)     page: 852-856   2018.9

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  137. Anomalous Sound Event Detection Based on WaveNet

    Hayashi Tomoki, Komatsu Tatsuya, Kondo Reishi, Toda Tomoki, Takeda Kazuya

    2018 26TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO)     page: 2494-2498   2018.9

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  138. Tsukuba Challenge 2017 Dynamic Object Tracks Dataset for Pedestrian Behavior Analysis

    Lambert Jacob, Liang Leslie, Morales Luis Yoichi, Akai Naoki, Carballo Alexander, Takeuchi Eijiro, Narksri Patiphon, Seiya Shunya, Takeda Kazuya

    JOURNAL OF ROBOTICS AND MECHATRONICS   Vol. 30 ( 4 ) page: 598-612   2018.8

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  139. End-to-End Autonomous Mobile Robot Navigation with Model-Based System Support

    Carballo Alexander, Seiya Shunya, Lambert Jacob, Darweesh Hatem, Narksri Patiphon, Morales Luis Yoichi, Akai Naoki, Takeuchi Eijiro, Takeda Kazuya

    JOURNAL OF ROBOTICS AND MECHATRONICS   Vol. 30 ( 4 ) page: 563-583   2018.8

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  140. Stereophonic Music Separation Based on Non-Negative Tensor Factorization with Cepstral Distance Regularization Reviewed

    Shogo Seki, Tomoki Toda, Kazuya Takeda

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   Vol. E101A ( 7 ) page: 1057 - 1064   2018.7

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    This paper proposes a semi-supervised source separation method for stereophonic music signals containing multiple recorded or processed signals, where synthesized music is focused on the stereophonic music. As the synthesized music signals are often generated as linear combinations of many individual source signals and their respective mixing gains, phase or phase difference information between inter-channel signals, which represent spatial characteristics of recording environments, cannot be utilized as acoustic clues for source separation. Non-negative Tensor Factorization (NTF) is an effective technique which can be used to resolve this problem by decomposing amplitude spectrograms of stereo channel music signals into basis vectors and activations of individual music source signals, along with their corresponding mixing gains. However, it is difficult to achieve sufficient separation performance using this method alone, as the acoustic clues available for separation are limited. To address this issue, this paper proposes a Cepstral Distance Regularization (CDR) method for NTF-based stereo channel separation, which involves making the cepstrum of the separated source signals follow Gaussian Mixture Models (GMMs) of the corresponding the music source signal. These GMMs are trained in advance using available samples. Experimental evaluations separating three and four sound sources are conducted to investigate the effectiveness of the proposed method in both supervised and semi-supervised separation frameworks, and performance is also compared with that of a conventional NTF method. Experimental results demonstrate that the proposed method yields significant improvements within both separation frameworks, and that cepstral distance regularization provides better separation parameters.

    DOI: 10.1587/transfun.E101.A.1057

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  141. Integrating driving behavior and traffic context through signal symbolization for data reduction and risky lane change detection

    Ekim Yurtever, Suguru Yamazaki, Chiyomi Miyajima, Chiyomi, Kazuya Takeda, Masataka Mori, Kentarou Hitomi, and Masumi Egawa

    IEEE Transactions on Intelligent Vehicles     page: 00   2018.6

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    (accepted).

  142. Retrieving a Driving Model Based on Clustered Intersection Data

    Sama Kyle, Morales Yoichi, Akai Naoki, Takeuchi Eijiro, Takeda Kazuya

    2018 3RD INTERNATIONAL CONFERENCE ON CONTROL AND ROBOTICS ENGINEERING (ICCRE)     page: 222-226   2018.4

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  143. 畳み込み雑音除去自己符号化器と対数周波数領域スペクトル特徴を用いた楽曲音源強調 Reviewed

    大谷健登, 丹羽健太, 西野隆典, 武田一哉

    電子情報通信学会論文誌D   Vol. J101-D ( 3 ) page: 00   2018.3

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  144. ITSS Technical Activities Spotlight: Getting to Know the Naturalistic Driving Data Analytics Technical Committee [Technical Activities]

    Pujitha Gunaratne, Kazuya Takeda

    IEEE Intelligent Transportation Systems Magazine     page: 167-167   2018.1

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  145. Daily activity recognition with large-scaled real-life recording datasets based on deep neural network using multi-modal signals Reviewed

    Tomoki Hayashi, Masafumi Nishida, Norihide Kitaoka, Tomoki Toda, Kazuya Takeda

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   Vol. E101A ( 1 ) page: 199 - 210   2018.1

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    © 2018 The Institute of Electronics, Information and Communication Engineers. In this study, toward the development of smartphone-based monitoring system for life logging, we collect over 1,400 hours of data by recording including both the outdoor and indoor daily activities of 19 subjects, under practical conditions with a smartphone and a small camera. We then construct a huge human activity database which consists of an environmental sound signal, triaxial acceleration signals and manually annotated activity tags. Using our constructed database, we evaluate the activity recognition performance of deep neural networks (DNNs), which have achieved great performance in various fields, and apply DNN-based adaptation techniques to improve the performance with only a small amount of subject-specific training data. We experimentally demonstrate that; 1) the use of multi-modal signal, including environmental sound and triaxial acceleration signals with a DNN is effective for the improvement of activity recognition performance, 2) the DNN can discriminate specified activities from a mixture of ambiguous activities, and 3) DNN-based adaptation methods are effective even if only a small amount of subject-specific training data is available.

    DOI: 10.1587/transfun.E101.A.199

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  146. Modeling Driver Risk Perception on City Roads Using Deep Learning Reviewed

    Peng Ping, Yuan Sheng, Wenhu Qin, Chiyomi Miyajima, Kazuya Takeda

    IEEE Access   Vol. 6   page: 68850 - 68866   2018

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    © 2013 IEEE. Research on how risk is perceived by drivers is vital to driving behavior research and driving safety. As risk can be divided into subjective and objective risk, in this paper, we focus on modeling subjective risk perception by drivers using a deep learning method. Different drivers often perceive different levels of subjective risk under the same driving conditions. In addition, different driving conditions or driving events will have different effects on drivers. Based on these two risk perception features, in this paper, we first design an experiment on a city road with two lanes to assess the level of subjective risk perceived by drivers belonging to different groups. We then use a deep learning network-based method to abstract features of the driving environment. These environmental features are integrated with driver risk perception data and this information is used as training and testing data for the learning network. Finally, a long-short-term memory-based method is adopted to model the subjective risk perception of individual drivers based on traffic conditions and vehicle operation data from the driver's vehicle. Our results show that the proposed method can effectively model the subjective risk perception behavior of drivers, allowing for end-to-end risk perception prediction in future driving assistance systems.

    DOI: 10.1109/ACCESS.2018.2879887

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  147. Recognizing emotions from speech using a physical model Reviewed

    Norihide Kitaoka, Shuhei Segawa, Ryota Nishimura, Kazuya Takeda

    Acoustical Science and Technology   Vol. 39 ( 2 ) page: 167 - 170   2018

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    DOI: 10.1250/ast.39.167

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  148. Learning How to Drive in Blind Intersections from Human Data Reviewed

    Kyle Sama, Yoichi Morales, Naoki Akai, Eijiro Takeuchi, Kazuya Takeda

    Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018     page: 317 - 324   2018

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    © 2018 IEEE. In this paper we present a method to learn how to drive in different types of blind intersections using expert driving data. We cluster different intersections based on the velocity of how drivers approach them, and train a linear SVM classifier for each class of intersection. Through clustering we found that there were three different classes of intersections in typical residential areas in Japan. We used inverse reinforcement learning (IRL) to build a driving model for each type of intersection. The models were trained from 308 trajectories traversed by 5 different drivers. The models and policies were implemented and evaluated in a ROS simulator where the agent is provided a global path, and upon it reaching an intersection, it selects the appropriate trained policy. By doing this, the simulated autonomous vehicle can perform proactive safe driving behaviors when approaching blind intersections.

    DOI: 10.1109/SMC.2018.00064

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  149. Multi-head decoder for end-to-end speech recognition Reviewed

    Tomoki Hayashi, Shinji Watanabe, Tomoki Toda, Kazuya Takeda

    Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH   Vol. 2018-September   page: 801 - 805   2018

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    © 2018 International Speech Communication Association. All rights reserved. This paper presents a new network architecture called multi-head decoder for end-to-end speech recognition as an extension of a multi-head attention model. In the multi-head attention model, multiple attentions are calculated, and then, they are integrated into a single attention. On the other hand, instead of the integration in the attention level, our proposed method uses multiple decoders for each attention and integrates their outputs to generate a final output. Furthermore, in order to make each head to capture the different modalities, different attention functions are used for each head, leading to the improvement of the recognition performance with an ensemble effect. To evaluate the effectiveness of our proposed method, we conduct an experimental evaluation using Corpus of Spontaneous Japanese. Experimental results demonstrate that our proposed method outperforms the conventional methods such as location-based and multi-head attention models, and that it can capture different speech/linguistic contexts within the attention-based encoder-decoder framework.

    DOI: 10.21437/Interspeech.2018-1655

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    arXiv

    Other Link: http://arxiv.org/pdf/1804.08050v2

  150. An investigation of multi-speaker training for WaveNet vocoder

    T. Hayashi, A. Tamamori, K. Kobayashi, K. Takeda, T. Toda

    Proc. ASRU     page: 712-718   2017.12

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  151. Investigation of effectiveness on recurrent neural network for daily activity recognition using multi-modal signals

    A. Tamamori, T. Hayashi, T. Toda, K. Takeda

    Proc. APSIPA     page: 7   2017.12

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    7 pages, Kuala Lumpur, Malaysia, Dec. 2017 (Invited Talk in Special Session).

  152. An Investigation of Recurrent Neural Network for Daily Activity Recognition using Multi-modal Signals

    Tamamori Akira, Hayashi Tomoki, Toda Tomoki, Takeda Kazuya

    2017 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC 2017)     page: 1334-1340   2017.12

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  153. Involvement of poly-rC binding proteins in posttranscriptional regulation of Sortilin, the cytokine trafficking mediator Reviewed

    Toshiki Yabe-Wada, Shintaro Matsuba, Kazuya Takeda, Akira Nakamura, Caroline C. Philpott, Nobuyuki Onai

    CYTOKINE   Vol. 100   page: 145 - 146   2017.12

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  154. Duration-controlled LSTM for polyphonic sound event detection

    T. Hayashi, S. Watanabe, T. Toda, T. Hori, J. Le Roux, K. Takeda.

    IEEE/ACM Transactions on Audio, Speech, and Language Processing   Vol. 25 ( 11 ) page: 2059-2070   2017.11

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  155. Duration-Controlled LSTM for Polyphonic Sound Event Detection Reviewed

    Tomoki Hayashi, Shinji Watanabe, Tomoki Toda, Takaaki Hori, Jonathan Le Roux, Kazuya Takeda

    IEEE/ACM Transactions on Audio Speech and Language Processing   Vol. 25 ( 11 ) page: 2059 - 2070   2017.11

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    © 2014 IEEE. This paper presents a new hybrid approach called duration-controlled long short-term memory (LSTM) for polyphonic sound event detection (SED). It builds upon a state-of-the-art SED method that performs frame-by-frame detection using a bidirectional LSTM recurrent neural network (BLSTM), and incorporates a duration-controlled modeling technique based on a hidden semi-Markov model. The proposed approach makes it possible to model the duration of each sound event precisely and to perform sequence-by-sequence detection without having to resort to thresholding, as in conventional frame-by-frame methods. Furthermore, to effectively reduce sound event insertion errors, which often occur under noisy conditions, we also introduce a binary-mask-based postprocessing that relies on a sound activity detection network to identify segments with any sound event activity, an approach inspired by the well-known benefits of voice activity detection in speech recognition systems. We conduct an experiment using the DCASE2016 task 2 dataset to compare our proposed method with typical conventional methods, such as nonnegative matrix factorization and standard BLSTM. Our proposed method outperforms the conventional methods both in an event-based evaluation, achieving a 75.3% F1 score and a 44.2% error rate, and in a segment-based evaluation, achieving an 81.1% F1 score, and a 32.9% error rate, outperforming the best results reported in the DCASE2016 task 2 Challenge.

    DOI: 10.1109/TASLP.2017.2740002

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  156. A Single-Dimensional Interface for Arranging Multiple Audio Sources in Three-Dimensional Space

    Kento Ohtani, Kenta Niwa, Kazuya Takeda

    IEICE TRANSACTIONS on Information and Systems (0.411),   Vol. E100-D ( 10 ) page: pp. 2635-264   2017.10

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  157. A single-dimensional interface for arranging multiple audio sources in three-dimensional space Reviewed

    Kento Ohtani, Kenta Niwa, Kazuya Takeda

    IEICE Transactions on Information and Systems   Vol. E100D ( 10 ) page: 2635 - 2643   2017.10

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    Copyright © 2017 The Institute of Electronics, Information and Communication Engineers. A single-dimensional interface which enables users to obtain diverse localizations of audio sources is proposed. In many conventional interfaces for arranging audio sources, there are multiple arrangement parameters, some of which allow users to control positions of audio sources. However, it is difficult for users who are unfamiliar with these systems to optimize the arrangement parameters since the number of possible settings is huge. We propose a simple, single-dimensional interface for adjusting arrangement parameters, allowing users to sample several diverse audio source arrangements and easily find their preferred auditory localizations. To select subsets of arrangement parameters from all of the possible choices, auditory-localization space vectors (ASVs) are defined to represent the auditory localization of each arrangement parameter. By selecting subsets of ASVs which are approximately orthogonal, we can choose arrangement parameters which will produce diverse auditory localizations. Experimental evaluations were conducted using music composed of three audio sources. Subjective evaluations confirmed that novice users can obtain diverse localizations using the proposed interface.

    DOI: 10.1587/transinf.2017EDP7028

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  158. Prediction Method for .Continuous Point Cloud Data Compression Using SLAM Information

    Chenxi Tu, Eijiro Takeuchi, Chiyomi Miyajima, and Kazuya Takeda

    fast-zero     page: SLAM Information," fast-zero, Sep., 2017   2017.9

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  159. Evaluation of Deep Learning-Based Driving Signal Generation Methods for Vehicle Control

    Shunya Seiya, Daiki Hayashi, Eijiro Takeuchi, Chiyomi Miyajima and Kazuya Takeda

    Fast-ZERO, 2017     page: 00   2017.9

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  160. Estimating Risk Levels Perceived by Individuals for Lane Change Scenes,"The fourth International Symposium on Future Active Safety Technology Toward zero traffic accidents

    Naren Bao, Chiyomi Miyajima, Eijiro Takeuchi, Kazuya Takeda, Shinichiro Honda, Toshiya Yoshitani, and Masayoshi Ito

    The fourth International Symposium on Future Active Safety Technology Toward zero traffic accidents     page: 00   2017.9

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  161. Missing component restoration for masked speech signals based on time-domain spectrogram factorization

    Shogo Seki, Hirokazu Kameoka, Tomoki Toda, Kazuya Takeda

    MLSP2017     page: 6   2017.9

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  162. Estimation of driver's risk feeling toward driving environment using neural network

    Yuan Sheng, Yiyang Li, Chiyomi Miyajima, Eijiro Takeuchi, Kazuya Takeda, Shinichiro Honda, Toshiya Yoshitani, and Masayoshi Ito

    FAST-zero '17     page: 00   2017.9

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    6pages

  163. Prediction method for continuous point cloud data compression using SLAM information

    Chenxi Tu, Eijiro Takeuchi, Chiyomi Miyajima, and Kazuya Takeda

    4th International Symposium on Future Active Safety Technology toward zero traffic accidents (FAST-zero '17)     page: 00   2017.9

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    6pages

  164. Speaker-dependent WaveNet vocoder

    Akira Tamamori,Tomoki Hayashi,Kazuhiro Kobayashi,Kazuya Takeda,Tomoki Toda,

    INTERSPEECH 2017     page: pp. 1118-1122   2017.8

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  165. Stereophonic Music Separation Based on Non-negative Tensor Factorization with Cepstrum Regularization

    Shogo Seki, Tomoki Toda, Kazuya Takeda

    EUSIPCO2017     page: pp. 1011-1015   2017.8

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  166. Stereophonic Music Separation Based on Non-negative Tensor Factorization with Cepstrum Regularization

    Seki Shogo, Toda Tomoki, Takeda Kazuya

    2017 25TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO)     page: 981-985   2017.8

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  167. Open Source Integrated Planner for Autonomous Navigation in Highly Dynamic Environments

    Darweesh Hatem, Takeuchi Eijiro, Takeda Kazuya, Ninomiya Yoshiki, Sujiwo Adi, Morales Luis Yoichi, Akai Naoki, Tomizawa Tetsuo, Kato Shinpei

    JOURNAL OF ROBOTICS AND MECHATRONICS   Vol. 29 ( 4 ) page: 668-684   2017.8

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  168. Continuous point cloud data compression using SLAM based prediction Reviewed

    Chenxi Tu, Eijro Takeuchi, Chiyomi Miyajima, Kazuya Takeda

    IEEE 2017 Intelligent Vehicles Symposium (IV '17)     page: 1744–1751   2017.6

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  169. Music Staging AI

    Kenta Niwa, Kento Ohtani, Kazuya Takeda

    2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017)     page: 6588-6589   2017.5

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  170. BLSTM-HMM hybrid system combined with sound activity detection network for polyphonic sound event detection Reviewed

    T. Hayashi, S. Watanabe, T. Toda, T. Hori, J. Le Roux, K. Takeda.

    Proc. ICASSP     page: 766-770   2017.3

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  171. Signal Processing for Smart Vehicle Technologies: Part 2 [From the Guest Editors] Reviewed

    John H.L. Hansen, Kazuya Takeda, Sanjeev M. Naik, Mohan M. Trivedi, Gerhard U. Schmidt, Yingying Jennifer Chen, Wade Trappe

    IEEE Signal Processing Magazine   Vol. 34 ( 2 ) page: 18 - 21   2017.3

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    DOI: 10.1109/MSP.2017.2650299

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  172. AN INVESTIGATION OF MULTI-SPEAKER TRAINING FORWAVENET VOCODER Reviewed

    Hayashi Tomoki, Tamamori Akira, Kobayashi Kazuhiro, Takeda Kazuya, Toda Tomoki

    2017 IEEE AUTOMATIC SPEECH RECOGNITION AND UNDERSTANDING WORKSHOP (ASRU)     page: 712-718   2017

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  173. BLSTM-HMM HYBRID SYSTEM COMBINED WITH SOUND ACTIVITY DETECTION NETWORK FOR POLYPHONIC SOUND EVENT DETECTION Reviewed

    Hayashi Tomoki, Watanabe Shinji, Toda Tomoki, Hori Takaaki, Le Roux Jonathan, Takeda Kazuya

    2017 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)     page: 766-770   2017

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  174. Continuous Point Cloud Data Compression Using SLAM Based Prediction Reviewed

    Tu Chenxi, Takeuchi Eijiro, Miyajima Chiyomi, Takeda Kazuya

    2017 28TH IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV 2017)     page: 1744-1751   2017

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  175. MISSING COMPONENT RESTORATION FOR MASKED SPEECH SIGNALS BASED ON TIME-DOMAIN SPECTROGRAM FACTORIZATION Reviewed

    Seki Shogo, Kameoka Hirokazu, Toda Tomoki, Takeda Kazuya

    2017 IEEE 27TH INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING     page: .   2017

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  176. MUSIC STAGING AI Reviewed

    Niwa Kenta, Ohtani Kento, Takeda Kazuya

    2017 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)     page: 6588-6589   2017

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  177. Speaker-dependent WaveNet vocoder Reviewed

    Akira Tamamori, Tomoki Hayashi, Kazuhiro Kobayashi, Kazuya Takeda, Tomoki Toda

    Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH   Vol. 2017-August   page: 1118 - 1122   2017

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    Copyright © 2017 ISCA. In this study, we propose a speaker-dependent WaveNet vocoder, a method of synthesizing speech waveforms with WaveNet, by utilizing acoustic features from existing vocoder as auxiliary features of WaveNet. It is expected that WaveNet can learn a sample-by-sample correspondence between speech waveform and acoustic features. The advantage of the proposed method is that it does not require (1) explicit modeling of excitation signals and (2) various assumptions, which are based on prior knowledge specific to speech. We conducted both subjective and objective evaluation experiments on CMU-ARCTIC database. From the results of the objective evaluation, it was demonstrated that the proposed method could generate high-quality speech with phase information recovered, which was lost by a mel-cepstrum vocoder. From the results of the subjective evaluation, it was demonstrated that the sound quality of the proposed method was significantly improved from mel-cepstrum vocoder, and the proposed method could capture source excitation information more accurately.

    DOI: 10.21437/Interspeech.2017-314

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  178. Impact of acoustic similarity on efficiency of verbal information transmission via subtle prosodic cues Reviewed

    Bohan Chen, Norihide Kitaoka, Kazuya Takeda

    Eurasip Journal on Audio, Speech, and Music Processing   Vol. 2016 ( 1 )   2016.12

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    © 2016, The Author(s). In this study, we investigate the effect of tiny acoustic differences on the efficiency of prosodic information transmission. Study participants listened to textually ambiguous sentences, which could be understood with prosodic cues, such as syllable length and pause length. Sentences were uttered in voices similar to the participant’s own voice and in voices dissimilar to their own voice. The participants then identified which of four pictures the speaker was referring to. Both the eye movement and response time of the participants were recorded. Eye tracking and response time results both showed that participants understood the textually ambiguous sentences faster when listening to voices similar to their own. The results also suggest that tiny acoustic features, which do not contain verbal meaning can influence the processing of verbal information.

    DOI: 10.1186/s13636-016-0097-6

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  179. Investigation on Recurrent Neural Network Architectures for Daily Activity Recognition Reviewed

    Akira Tamamori, Tomoki Hayashi, Tomoki Toda, Kazuya Takeda

    The 3rd International Conference on Universal Village (UV2016)     page: 00   2016.12

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  180. Sound enhancement system using selective binary filtering Reviewed

    Tomomi Suzuki, Takanori Nishino, Yoshio Ishiguro, Kazuya Takeda

    5th Joint Meeting of the ASA and ASJ     page: 00   2016.12

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  181. Convolutional Biderectional LSTM-HMM Hybrid System for Polyphonic Sound Event Detection Reviewed

    Tomoki Hayashi, Shinji Watanabe, Tomoki Toda, Takaaki Hori, Jonathan Le Roux, Kazuya Takeda

    5th Joint Meeting of the ASA and ASJ     page: 00   2016.12

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  182. Signal Processing for Smart Vehicle Technologies [From the Guest Editors]

    John H.L. Hansen, Kazuya Takeda, Sanjeev M. Naik, Mohan M. Trivedi, Gerhard U. Schmidt, Yingying Chen

    IEEE Signal Processing Magazine   Vol. 33 ( 6 ) page: 12 - 13   2016.11

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    DOI: 10.1109/MSP.2016.2600624

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  183. Compressing Continuous Point Cloud Data Using Image Compression Methods Reviewed

    Chenxi Tu, Eijiro Takeuchi, Chiyomi Miyajima, Kazuya Takeda

    ITSC2016     page: 00   2016.11

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  184. AI framework to arrange audio objects according to listener preferences Reviewed

    Kento Ohtani, Kenta Niwa, Kazuya Takeda

    5th Joint Meeting of the Acoustical Society of America and Acoustical Society of Japan     page: 00   2016.11

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  185. Stereo Channel Music Signal Separation Based on Nonnegative Tensor Factorization with Cepstrum Regularization Reviewed

    Shogo Seki, Kento Ohtani, Tomoki Toda, Kazuya Takeda

    5th Joint Meeting of the ASA and ASJ     page: 00   2016.11

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  186. Driver-Behavior Modeling Using On-Road Driving Data: A new application for behavior signal processing Reviewed

    Chiyomi Miyajima, Kazuya Takeda

    IEEE Signal Processing Magazine   Vol. 33 ( 6 ) page: 14 - 21   2016.11

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    © 2016 IEEE. This article reviews data-centric approaches for statistical modeling of driver behavior. Modeling driver behavior is challenging due to its stochastic nature and the high degree of inter- and intradriver variability. One way to deal with the highly variable nature of driving behavior is to employ a data-centric approach that models driver behavior using large amounts of driving data collected from numerous drivers in a variety of traffic conditions. To obtain large amounts of realistic driving data, several projects have collected real-world driving data. Statistical machine-learning techniques, such as hidden Markov models (HMMs) and deep learning, have been successfully applied to model driver behavior using large amounts of driving data. We have also collected on-road data recording hundreds of drivers over more than 15 years. We have applied statistical signal processing and machine-learning techniques to this data to model various aspects of driver behavior, e.g., driver pedal-operation, car-following, and lane-change behaviors for predicting driver behavior and detecting risky driver behavior and driver frustration. By reviewing related studies and providing concrete examples of our own research, this article is intended to illustrate the usefulness of such data-centric approaches for statistical driver-behavior modeling.

    DOI: 10.1109/MSP.2016.2602377

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  187. Analysis of driver workload when using speech interfaces Reviewed

    D Hayashi, C Miyajima, K Takeda

    The Journal of the Acoustical Society of America   Vol. 140 ( 4 ) page: 2961 - 2961   2016.10

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  188. Projection of a virtual speaker into a vehicle using sound field control Reviewed

    T Yamamura, Y Ishiguro, T Nishino, K Takeda

    The Journal of the Acoustical Society of America   Vol. 140 ( 4 ) page: 3063 - 3063   2016.10

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  189. Emotion recognition from speech using a physical model Reviewed

    Norihide Kitaoka, Shuhei Segawa, Kazuya Takeda

    Proc. ICA2016     page: 00   2016.9

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  190. Bidirectional LSTM-HMM Hybrid System for Polyphonic Sound Event Detection Reviewed

    Tomoki Hayashi, Shinji Watanabe, Tomoki Toda, Takaaki Hori, Jonathan Le Roux, Kazuya Takeda

    DCASE2016     page: 00   2016.9

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  191. Investigation of DNN-based modeling for audio-visual speech recognition Reviewed

    Satoshi Tamura, Hiroshi Ninomiya, Norihide Kitaoka, Shin Osuga, Yurie Iribe, Kazuya Takeda, Satoru Hayamizu

    2015 First International Workshop on Spoken Language Processing (MLSLP2015)     page: 00   2016.9

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  192. Investigation on Recurrent Neural Network Architectures for Daily Activity Recognition Reviewed

    Akira Tamamori, Tomoki Hayashi, Tomoki Toda, Kazuya Takeda

    UV2016     page: 00   2016.9

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  193. Recurrent Neural Networkに基づく日常生活行動認識

    玉森 聡、林 知樹、戸田 智基、武田 一哉

    電子情報通信学会技術報告   Vol. 116(189) ( 7 ) page: 12   2016.8

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  194. Accelerated Deformable Part Models on GPUs Reviewed

    Manato Hirabayashi, Shinpei Kato, Masato Edahiro, Kazuya Takeda, Seiichi Mita

    IEEE Transactions on Parallel and Distributed Systems   Vol. 27 ( 6 ) page: 1589 - 1602   2016.6

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    © 2015 IEEE. Object detection is a fundamental challenge facing intelligent applications. Image processing is a promising approach to this end, but its computational cost is often a significant problem. This paper presents schemes for accelerating the deformable part models (DPM) on graphics processing units (GPUs). DPM is a well-known algorithm for image-based object detection, and it achieves high detection rates at the expense of computational cost. GPUs are massively parallel compute devices designed to accelerate data-parallel compute-intensive workload. According to an analysis of execution times, approximately 98 percent of DPM code exhibits loop processing, which means that DPM could be highly parallelized by GPUs. In this paper, we implement DPM on the GPU by exploiting multiple parallelization schemes. Results of an experimental evaluation of this GPU-accelerated DPM implementation demonstrate that the best scheme of GPU implementations using an NVIDIA GPU achieves a speed up of 8.6x over a naive CPU-based implementation.

    DOI: 10.1109/TPDS.2015.2453962

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  195. Prediction of Individual Driving Behavior on Highway Curves

    Naren Bao, Daiki Hayashi, Chiyomi Miyajima, and Kazuya Takeda

    The third Workshop on Natural- istic Driving Data Analysitics, IEEE Intelligent Vehicles Symposium     page: 00   2016.6

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  196. Integrating driving behavior and traffic context through signal symbolization. Reviewed

    Yamazaki, S., Miyajima, C., Yurtsever, E., Takeda, K., Mori, M., Hitomi, K., & Egawa, M.

    In Intelligent Vehicles Symposium (IV), 2016 IEEE.     page: pp. 642-647   2016.6

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  197. Classification of driver's neutral and cognitive distraction states based on peripheral vehicle behavior in driver's gaze transition Reviewed

    Takatsugu Hirayama, Kenji Mase, Chiyomi Miyajima, Kazuya Takeda

    IEEE Transactions on Intelligent Vehicles   Vol. 1 ( 2 ) page: 148 - 157   2016.6

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    © 2016 IEEE. To support safe driving, numerous methods of detecting distractions using measurements of a driver's gaze have been proposed. These methods empirically focused on certain driving contexts and analyzed gaze behavior under particular peripheral vehicle conditions; therefore, numerous driving situations were not considered. To address this problem with hypothesis-testing approaches, we turn the problem around and propose a data-mining approach that analyzes peripheral vehicle behavior during gaze transitions of drivers in order to compare their neutral driving state with a cognitive distraction state. This change in thinking is the first contribution of this paper. The analysis results show that under the neutral condition, drivers generally turned their gaze to peripheral vehicles to be focused on; however, they did not do this consistently under the distracted condition. As the second contribution, we propose a simple classifier to discriminate between the cognitive distraction and neutral states by analyzing the peripheral vehicle behavior. The proposed classifier can manage various situations and provide high classification accuracy by focusing on gaze transitions from the front view toward other directions.

    DOI: 10.1109/TIV.2016.2599786

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  198. Daily activity recognition based on acoustic signals and acceleration signals estimated with Gaussian process Reviewed

    Masafumi Nishida, Norihide Kitaoka, Kazuya Takeda

    2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2015     page: 279 - 282   2016.2

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    © 2015 Asia-Pacific Signal and Information Processing Association. We have created corpus of daily activities using wearable sensors. The corpus consists of sound and image data from a camera and motion signals from a smartphone for both indoor and outdoor activities over 72 continuous hours. We propose a method that can interpolate acceleration signals to any sample points with a Gaussian process in order to recognize daily activities. We conducted recognition experiments of daily activities using our corpus. Experimental results showed that the proposed method can improve recognition accuracy compared to a conventional method. This demonstrates the effectiveness of estimating acceleration signals with a Gaussian process to recognize daily activities.

    DOI: 10.1109/APSIPA.2015.7415520

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  199. Audio-visual speech recognition using deep bottleneck features and high-performance lipreading Reviewed

    Satoshi Tamura, Hiroshi Ninomiya, Norihide Kitaoka, Shin Osuga, Yurie Iribe, Kazuya Takeda, Satoru Hayamizu

    2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2015     page: 575 - 582   2016.2

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    © 2015 Asia-Pacific Signal and Information Processing Association. This paper develops an Audio-Visual Speech Recognition (AVSR) method, by (1) exploring high-performance visual features, (2) applying audio and visual deep bottleneck features to improve AVSR performance, and (3) investigating effectiveness of voice activity detection in a visual modality. In our approach, many kinds of visual features are incorporated, subsequently converted into bottleneck features by deep learning technology. By using proposed features, we successfully achieved 73.66% lipreading accuracy in speaker-independent open condition, and about 90% AVSR accuracy on average in noisy environments. In addition, we extracted speech segments from visual features, resulting 77.80% lipreading accuracy. It is found VAD is useful in both audio and visual modalities, for better lipreading and AVSR.

    DOI: 10.1109/APSIPA.2015.7415335

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  200. Tracking driver signage observation using local feature matching and optical flow Reviewed

    Chiyomi Miyajima, Katsuya Sakoyama, Kazuya Takeda

    2015 IEEE/SICE International Symposium on System Integration, SII 2015     page: 479 - 482   2016.2

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    © 2015 IEEE. We investigate a method for identifying objects observed by drivers. Here we focus on roadside signage as an example, and track the driver's observation of signage while driving. A gaze tracking system and a forward-directed video camera are used to determine the driver's region of interest (ROI). The driver's observation of signage is detected by tracking the driver's ROI using optical flow, and by matching the driver's ROI with template images of signboards in a signage database using local feature matching. Driver and signage location information are used to limit candidate signboards for reducing computational cost for image matching. We conduct an experiment to evaluate our method and achieve a 66.2% detection rate of drivers' signboard observation with a false positive rate of 6.6%.

    DOI: 10.1109/SII.2015.7405026

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  201. Modeling and detecting excessive trust from behavior signals: Overview of research project and results Reviewed

    Kazuya Takeda

    Human-Harmonized Information Technology, Volume 1: Vertical Impact     page: 57 - 75   2016.1

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    © Springer Japan 2016. An approach which would allow us to better understand behavioral states inherent in observed behaviors is proposed, based on the development of a mathematical representation of driving behaviors signals using our large driving behavior signal corpus. In particular, the project is aimed at developing technologies for preventing excessive trust in users of automated systems. Misuse/disuse of automation is introduced as a cognitive model of excessive trust, and methods of quantitative measurement are devised. PWARX and GMM models are proposed to represent discrete and continuous information in the cognition/decision/action process. We also develop a method of modeling visual behavior aiming at understanding environmental awareness while driving. We showed the effectiveness of the model experimentally through risky lane change detection. Finally, we show the effectiveness of the method to quantify excessive trust based on developed technology.

    DOI: 10.1007/978-4-431-55867-5_3

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  202. Robust example search using bottleneck features for example-based speech enhancement Reviewed

    Atsunori Ogawa, Shogo Seki, Keisuke Kinoshita, Marc Delcroix, Takuya Yoshioka, Tomohiro Nakatani, Kazuya Takeda

    Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH   Vol. 08-12-September-2016   page: 3733 - 3737   2016

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    Copyright © 2016 ISCA. Example-based speech enhancement is a promising approach for coping with highly non-stationary noise. Given a noisy speech input, it first searches in noisy speech corpora for the noisy speech examples that best match the input. Then, it concatenates the clean speech examples that are paired with the matched noisy examples to obtain an estimate of the underlying clean speech component in the input. This framework works well if the noisy speech corpora contain the noise included in the input. However, it is impossible to prepare corpora that cover all types of noisy environments. Moreover, the example search is usually performed using noise sensitive mel-frequency cepstral coefficient features (MFCCs). Consequently, a mismatch between an input and the corpora is inevitable. This paper proposes using bottleneck features (BNFs) extracted from a deep neural network (DNN) acoustic model for the example search. Since BNFs have good noise robustness (invariance), the mismatch is mitigated and thus a more accurate example search can be performed. Experimental results on the Aurora4 corpus show that the example-based approach using BNFs greatly improves the enhanced speech quality compared with that using MFCCs. It also consistently outperforms a conventional DNN-based approach, i.e. a denoising autoencoder.

    DOI: 10.21437/Interspeech.2016-671

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  203. Symbolization for Large-Scale Driving Corpus and Its Applications Reviewed

    Egawa, Masumi Mori, Masataka Takenaka, Kazuhito Bando, Takashi Taniguchi, Tadahiro Miyajima, Chiyomi Takeda, Kazuya

    Transactions of Society of Automotive Engineers of Japan   Vol. 47 ( 5 ) page: 1135 - 1140   2016

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  204. Compressing Continuous Point Cloud Data Using Image Compression Methods

    Tu Chenxi, Takeuchi Eijiro, Miyajima Chiyomi, Takeda Kazuya

    2016 IEEE 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC)     page: 1712 - 1719   2016

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  205. Relationship between Speaker/Listener Similarity and Information Transmission Quality in Speech Communication Reviewed

    Bohan Chen, Norihide Kitaoka, Kazuya Takeda

    APSIPA ASC 2015     page: 00   2015.12

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  206. Audio-visual speech recognition using deep bottleneck features and high-perfromanc lipreading Reviewed

    Satoshi Tamura, Hiroshi Ninomiya, Norihide Kitaoka, Shin Osuga, Yurie Iribe, Kazuya Takeda, Satoru Hayamizu

    APSIPA ASC 2015     page: 00   2015.12

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  207. Daily activity recognition based on acoustic signals and acceleration signals estimated with Gaussian process, Reviewed

    Masafumi Nishida, Norihide Kitaoka, Kazuya Takeda

    APSIPA ASC 2015     page: 00   2015.12

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  208. Tracking driver's observation using local feature matching and optical flow Reviewed

    Chiyomi Miyajima, Katsuya Sakoyama, Kazuya Takeda

    IEEE/SICE International Symbposium on System Integration (SII 2015)     page: 00   2015.12

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  209. Development and evaluation of spherical microphone baffle with two hollows for binaural recording Reviewed

    Taishi Nakagiri, Toshiki Yamamura, Takanori Nishino, Hiroshi Naruse, and Kazuya Takeda

    Proc. 12th Western Pacific Acoustics Conference 2015 (WESPAC2015),     page: 00   2015.12

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  210. Single Dimensional Control of Spatial Audio Object Arrangement

    Kento Ohtani, Kenta Niwa, Kazuya Takeda

    12th Western Pacific Acoustics Conference 2015 (WESPAC2015)     page: 00   2015.12

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  211. Elderly person's emotional state estimation in conversation based on speech features for spoken dialogue systems Reviewed

    Shuhei Segawa, Norihide Kitaoka, Kazuya Takeda

    12th Western pacific Acoustics Conference 2015 (WESPAC2015)     page: 00   2015.12

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  212. Tracking driver's observation using local feature matching and optical flow Reviewed

    Chiyomi Miyajima,Katsuya Sakoyama, and Kazuya Takeda

    2015 IEEE/SICE International Symposium on System Integration     page: 00   2015.12

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  213. An Open Approach to Autonomous Vehicles

    S. Kato, E. Takeuchi, Y. Ishiguro, Y. Ninomiya, K. Takeda and T. Hamada

    IEEE Micro   Vol. 35 ( 6 ) page: 60-68   2015.12

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  214. Driving Scene Classification Using Vehicle Motion Estimated with Smartphone

    Masayuki Tsuboi,Chiyomi Miyajima,Kazuya Takeda

    The 7th Biennial Workshop on Digital Signal Processing for In-Vehicle Systems     page: 00   2015.10

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  215. Effect of speaking rate and speech complexity on transmission quality during driving navigation task Reviewed

    Bohan Chen, Norihide Kitaoka, Kazuya Takeda

    DSP in Vehicle 2015     page: 00   2015.10

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  216. Audio-visual processing toward robust speech recognition in cars Reviewed

    Satoshi Tamura, Hiroshi Ninomiya, Norihide Kitaoka, Shin Osuga, Yurie Iribe, Kazuya Takeda, Satoru Hayamizu

    7th Biennial Workshop on DSP for In-Vehicle Systems and Safety     page: 00   2015.10

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  217. Risky Lane Change Detection Based on Symbolization of Driving Data Reviewed

    Suguru Yamazaki,Chiyomi Miyajima,Masataka Mori,Takashi Bando,Kazuhito Takenaka,and Kazuya Takeda

    The 7th Biennial Workshop on Digital Signal Processing for In-Vehicle Systems     page: 00   2015.10

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  218. Integration of acoustic information in Google Street View using a spherical microphone array Reviewed

    Tomomi Suzuki, Yoshio Ishiguro, Takanori Nishino, and Kazuya Takeda

    Proc. AUN/SEED-Net Regional Conference for Computer and Information Engineering 2015 (RCCIE 2015),     page: 00   2015.10

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  219. Modelling of Physical Characteristics of Speech under Stress Reviewed

    Xiao Yao,Takatoshi Jitsuhiro,Chiyomi Miyajima,Norihide Kitaoka,and Kazuya Takeda

    IEEE Signal Processing Letters   Vol. 22 ( 10 ) page: 1801-1805   2015.10

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    DOI: 10.1109/LSP.2015.2434732

  220. Investigation of DNN-based audio-visual speech recognition Reviewed

    Satoshi Tamura, Hiroshi Ninomiya, Norihide Kitaoka, Shin Osuga, Yurie Iribe, Kazuya Takeda

    IEICE Trans. Inf. & Syst     page: 2444-2451   2015.9

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  221. Driving signature extraction Reviewed

    Ekim Yurtsever,Chiyomi Miyajima, Selpi Selpi, and Kazuya Takeda

    Proc.of 3rd International Symposium on Future Active Safety Technology towards zero traffic accidents,     page: 00   2015.9

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  222. Integration of Deep Bottleneck Features for Audio-Visual Speech Recognition Reviewed

    Hiroshi Ninomiya, Norihide Kitaoka, Satoshi Tamura, Yurie Iribe, Kazuya Takeda

    Proc. INTERSPEECH2015     page: 00   2015.9

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  223. Traffic trajectory history and drive path generation using GPS data cloud Reviewed

    Ekim Yurtsever,Chiyomi Miyajima, and Kazuya Takeda

    Proc. of IEEE Intelligent Vehicles Symposium     page: 00   2015.7

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  224. Analysis driver gaze behavior and consistency of decision making during automated driving Reviewed

    Chiyomi Miyajima,Suguru Yamazaki, Takashi Bando,Kentaro Hitomi,Hitoshi Terai,Hiroyuki Okuda,Takatsugu Hirayama,Masumi Egawa,Tatsuya Suzuki,and Kazuya Takeda

    2015IEEE Intelligent Vehicles Symposium   Vol. 4 ( 1 ) page: 59-66   2015.7

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  225. Automatic lane change extraction based on temporal patterns of symbolized driving behavioral data Reviewed

    Masataka Mori, Kazuhito Takenaka, Takashi Bando, Tadahiro Taniguchi,Chiyomi Miyajima, Kazuya Takeda

    Proc. of 2015 IEEE Intelligent Vehicles Symposium (IV '15)     page: 00   2015.6

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  226. Analyzing driver gaze behavior and consistency of decision making during automated driving Reviewed

    Chiyomi Miyajima, Suguru Yamazaki, Takashi Bando, Kentarou Hitomi, Hitoshi Terai, Hiroyuki Okuda, Takatsugu Hirayama, Masumi Egawa, Tatsuya Suzuki, Kazuya Takeda

    Proc. of 2015 IEEE Intelligent Vehicles Symposium (IV '15)     page: 00   2015.6

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  227. Traffic trajectory history and drive path generation using GPS data cloud.

    Yurtsever, E., Takeda, K., & Miyajima, C.

    In Intelligent Vehicles Symposium (IV), 2015 IEEE     page: pp. 229-234   2015.6

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  228. 種々のテキスト検索モデルの頑健性向上による音声ドキュメント検索の高精度化 Reviewed

    市川賢、北岡教英、柘植覚、武田一哉、北研ニ

    情報処理学会論文誌   Vol. 56 ( 3 ) page: 00   2015.3

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  229. Tracking Roadside Signage Observed by Drivers Reviewed

    Katsuya Sakoyama, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    2015 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing     page: 00   2015.2

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  230. 相補ウィーナーフィルタを利用した残響抑圧手法に対するフィルタ係数推定手法 Reviewed

    大谷健登,小松達也,近藤多伸,西野隆典,武田一哉

    電子情報通信学会論文誌(A),電子情報通信分野における萌芽的研究小特集   Vol. J98-A ( 2 ) page: 178-189   2015.2

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  231. An evaluation method of aggressiveness of driving behavior using drive recorders Reviewed

    Yiyang Li, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    IEEJ Journal of Industry Applications   Vol. 4 ( 1 ) page: 59-66   2015

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  232. Noisy speech recognition using blind spatial subtraction array technique and deep bottleneck features Reviewed

    Norihide Kitaoka, Tomoki Hayashi, Kazuya Takeda

    APSIPA ASC 2014     page: 00   2014.12

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  233. Investigating the Robustness of Deep Bottleneck Features for Recognizing Speech of Speakers of Various Ages Reviewed

    Norihide Kitaoka, Tomoki Hayashi, Kazuya Takeda

    APSIPA 2014     page: 00   2014.12

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  234. Development and preliminary analysis of sensor signal database of contiuous daily living activity over the long term Reviewed

    Masafumi Nishida, Norihide Kitaoka, Kazuya Takeda

    APSIPA ASC 2014     page: 00   2014.12

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  235. Unsupervised energy disaggregation using conditional random fields Reviewed

    Panikos Heracleous, Pongtep Angkititrakul, Norihide Kitaoka, Kazuya Takeda

    IEEE ISGT Europe 2014     page: 00   2014.10

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  236. Measuring Aggressive Driving Behavior Using signals from drive recorders Reviewed

    Yiyang Li, Chiyomi Miyajima, Norihide Kitaoka, Kazuya Takeda

    IEEE ITSC14     page: 00   2014.10

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  237. Investigating the Robustness of Deep Bottleneck Features for Recognizing Speech of Speakers of Various Ages Reviewed

    Tomoki Hayashi, Chiyomi Miyajima, Takanori Nishino, Kazuya Takeda

    FORUM ACUSTICUM 2014     page: 00   2014.9

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  238. Sound image perception for a sound source moving in musical contents Reviewed

    Kento Ohtani, Takanori Nishino, Kazuya Takeda

    FORUM ACUSTICUM 2014     page: 00   2014.9

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  239. Building Driving Intelligence using Traffic Big Data Reviewed

    Kazuya Takeda

    2014 World Congress on Intelligent Transport Systems     page: 00   2014.9

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  240. 《特集》サイバーフィジカルシステム:フィールド実証実験(FOT)に向けて

    平野清美・武田一哉

    情報処理学会誌「情報処理」   Vol. 55 ( 9 ) page: 922-927   2014.8

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  241. 音声ドキュメント検索における種々の検討および線形補間係数を自動決定する検索質問拡張 Reviewed

    柘植覚、大橋宏正、市川賢、北岡教英、武田一哉、北研ニ

    情報処理学会論文誌   Vol. 55 ( 6 ) page: 1625-1636   2014.6

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  242. Adaptive dereverberation method based on complementary wiener filter and modulation transfer function Reviewed

    Kento Ohtani, Tatsuya Komatsu, Takanori Nishino, Kazuya Takeda

    REVERB workshop     page: 00   2014.5

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  243. Driving scene retrieval with an integrated similarity measure using driving behavior and environment information Reviewed

    Yiang Li,Chiyomi Miyajima,Norihide Kitaoka,Kazuya Takeda

    IEEJ Journal C,   Vol. 134 ( 5 ) page: 1-8   2014.5

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  244. Evalution method for aggressiveness of driving behavior using drive recorders, Reviewed

    Yiang Li,Chiyomi Miyajima,Norihide Kitaoka,Kazuya Takeda,

    IEEJ Journal of Industry Applications,   Vol. 4 ( 1 ) page: 00   2014.5

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  245. 発話セグメントクラスタの評価とそれに基づく改良ボトムアップクラスタリングによる話者ダイアライゼーションの高精度化

    陳伯翰, 北岡教英, 武田一哉

    電子情報通信学会論文誌(D)   Vol. J97-D ( 3 ) page: 540-547   2014.3

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  246. Effective Frame Selection for Blind Source Separation based on Frequency Domain Independent Component Analysis Reviewed

    Yusuke Mizuno,Takanori Nishino,Kazunobu Kondo,Norihide Kitaoka,Kazuya Takeda,

    IEICE Trans,Fundamentals,   Vol. E97-A ( 3 ) page: 784-791   2014.3

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  247. Use of driver gaze information for detecting risky lane changes Reviewed

    Masataka Mori, Chiyomi Miyajima, Takatsugu Hirayama, Norihide Kitaoka, and Kazuya Takeda

    2014 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP '14)     page: 00   2014.2

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  248. Effect of acoustic and linguistic contexts on human and machine speech recognition

    Norihide Kitaoka, Daisuke Enami, Seiichi Nakagawa

    Computer Speech and Language   Vol. 28   page: 767-787   2014.2

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  249. Improvement of multimodal gestrure and speech recognition performance using time intervals between gestures and accompaning speech

    Madoka Miki, Norihide Kitaoka, Chiyomi Miyajima, Takanori Nishino, Kazuya Takeda

    EURASIP Journal on Audio, Speech, and Music Processing   Vol. 2014 ( 2 ) page: 7pages   2014.1

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    DOI: 10.1186

  250. A graph-based spoken dialog strategy utilizing multiple understanding hypotheses

    Norihide Kitaoka, Yuji Kinoshita, Sunao Hara, Chiyomi Miyajima, Kazuya Takeda

    Information and Media Technologies   Vol. 29 ( 1 ) page: 1-10   2014.1

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  251. Driving scene retrieval with an integrated similarity measure using driving behavior and environment information

    Yiyang Li, Chiyomi Miyajima, Norihide Kitaoka, Kazuya Takeda

    IEEJ Journal C   Vol. 134 ( 5 ) page: 1-8   2014

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  252. 空間相関行列の固有値分布に着目した音源別距離推定 Reviewed

    丹羽健太, 江崎知, 日岡裕輔, 西野隆典, 武田一哉

    電子情報通信学会論文誌   Vol. J97-A ( 2 ) page: 68-76   2014

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  253. Effective Frame Selection for Blind Source Separation based on Frequency Domain Independent Component Analysis

    Yusuke Mizuno, Takanori Nishino, Kazunobu Kondo, Norihide Kitaoka, Kazuya Takeda

    IEICE Trans. Fundamentals   Vol. E97-A ( 3 ) page: 784-791   2014

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  254. Modeling driver gaze and vehicle operation behavior during lane changes Reviewed

    Masataka Mori, Chiyomi Miyajima, Takatsugu Hirayama, Norihide Kitaoka, and Kazuya Takeda

    International Joint Workshop on Advanced Sensing/Visual Attention and Interaction - Toward Creation of Human-Harmonized Information Technology (ASVAI 2013)     page: 00   2013.11

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  255. Spoken document retrieval using both word-based and syllable-based document spaces with latent semantci indexing Reviewed

    Ken Ichikawa, Satoru Tsuge, Norihide Kitaoka, Kazuya Takeda, Kenji Kita

    APSIPA ASC 2013     page: 00   2013.10

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  256. Toward the development of a driving support system for repressing overtrust and overreliance Reviewed

    Yusuke Tanaka, Takashi Bando, Masumi Egawa, Hiroyuki Okuda, Hitoshi Terai, Takatsugu Hirayama, Chiyomi Miyajima, Daisuke Deguchi, Katsuhiro Kaji, Kazuya Takeda, and Tatsuya Suzuki

    20th ITS World Congress 2013     page: 00   2013.10

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  257. Integrated modeling of driver gaze and vehicle operation behavior to estimate risk level during lane changes Reviewed

    Masataka Mori, Chiyomi Miyajima, Takatsugu Hirayama, Norihide Kitaoka, Kazuya Takeda

    Proc. IEEE ITSC 2013     page: 00   2013.10

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  258. Modeling driver gaze and vehicle operation patterns to estimate long-term risk levels of driving behavior Reviewed

    Masataka Mori, Chiyomi Miyajima, Takatatsugu Hirayama, Norihide Kitaoka, and Kazuya Takeda

    Sixth Biennial Workshop on Digital Signal Processing for In-Vehicle Systems (DSP in Vehicles 2013)     page: 00   2013.9

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  259. An audio-visual in-car corpus "CENSREC-2-AV" for robust bimodal speech recognition: DSP, human-to-vehicle interfaces, driver behavior, and safety Reviewed

    Takuya Kawasaki, Satoshi Tamura, Satoru Hayamizu, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    Sixth Biennial Workshop on Digital Signal Processing for In-Vehicle Systems (DSP in Vehicles 2013)     page: 00   2013.9

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  260. Toward well-balanced man-machine cooperation in vehicle Reviewed

    Kentarou Hitomi, Takashi Bando, Masumi Egawa, Hiroyuki Okuda, Hitoshi Terai, Takatsugu Hirayama, Chiyomi Miyajima, Daisuke Deguchi, Katsuhiro Kaji, Kazuya Takeda, and Tatsuya Suzuki,

    Sixth Biennial Workshop on Digital Signal Processing for In-Vehicle Systems (DSP in Vehicles 2013)     page: 00   2013.9

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  261. Adaptation techniques for stochastic driver-behavior modeling Reviewed

    Pongtep Angkititrakul, Chiyomi Miyajima, and Kazuya Takeda

    Sixth Biennial Workshop on Digital Signal Processing for In-Vehicle Systems (DSP in Vehicles 2013)     page: 00   2013.9

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  262. Analysis of driving behavior signals recorded from different types of vehicles using CAN and Smartphone Reviewed

    Chiyomi Miyajima, Hiroaki Ishikawa, Masataka Kaneko, Norihide Kitaoka, and Kazuya Takeda

    2nd International Symposium on Future Active Safety Technology toward zero traffic accidents (FAST-zero '13)     page: 00   2013.9

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  263. Comparison of lane change behavior of expert and non-expert drivers Reviewed

    Masataka Mori, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    2nd International Symposium on Future Active Safety Technology toward zero traffic accidents (FAST-zero '13)     page: 00   2013.9

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  264. Repressing overtrust: driver cooperated driving support systems Reviewed

    Takashi Bando, Masumi Egawa, Hiroyuki Okuda, Hitoshi Terai, Takatsugu Hirayama, Chiyomi Miyajima,Daisuke Deguchi, Katsuhiko Kaji, Kazuya Takeda, and Tatsuya Suzuki

    2nd International Symposium on Future Active Safety Technology toward zero traffic accidents (FAST-zero '13)     page: 00   2013.9

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  265. An integrated similarity measure for driving scene retrieval using driving behavior and environmental information Reviewed

    Yiyang Li, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    2nd International Symposium on Future Active Safety Technology toward zero traffic accidents (FAST-zero '13)     page: 00   2013.9

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  266. Prediction of context-dependent deceleration behavior Reviewed

    Pongtep Angkititrakul, Chiyomi Miyajima, and Kazuya Takeda

    2nd International Symposium on Future Active Safety Technology toward zero traffic accidents (FAST-zero '13)     page: 00   2013.9

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  267. Analysis of lane change maneuvers based on driver gaze and vehicle operation behavior Reviewed

    Masataka Mori, Chiyomi Miyajima, Takatsugu Hirayama, Norihide Kitaoka, and Kazuya Takeda

    International Conference on Driver Distraction and Inattention 2013, (DDI 2013)     page: 00   2013.9

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  268. Modeling Safety of Lane Change Maneuvers Based on Driver Gaze and Vehicle Operation Behavior Reviewed

    Masataka Mori, Chiyomi Miyajima, Takatsugu Hirayama, Norihide Kitaoka, Kazuya Takeda

    DDI 2013     page: 00   2013.9

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  269. Classification of speech under stress based on physical modeling

    Xiao Yao, Takatoshi Jitsuhiro, Chiyomi Miyajima, Norihide Kitaoka, Kazuya Takeda

    Acoustical Science and Technology   Vol. 34 ( 5 ) page: 311-321   2013.9

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  270. Modeling subjective evaluation of music similarity using tolerance Reviewed

    Shota Kawabuchi, Chiyomi Miyajima, Norihide Kitaoka, Kazuya Takeda

    Proc. EUSIPCO 2013     page: 00   2013.9

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  271. Measuring driving behavior on different types of vehicles Reviewed

    Chiyomi Miyajima, Hiroki Takeshita, Hiroaki Ishikawa, Norihide Kitaoka, Kazuya Takeda

    The SICE Annual Conference 201     page: 00   2013.9

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  272. Classification of speech under stress by modeling the aerodynamics of the laryngeal ventricle Reviewed

    Xiao Yao, Takatoshi Jitsuhiro, Chiyomi Miyajima, Norihide Kitaoka, Kazuya Takeda

    Proc. INTERSPEECH2013     page: 00   2013.8

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  273. Classification of speech under stress based on modeling of the vocal folds and vocal tract Reviewed

    Xiao Yao, Takatoshi Jitsuhiro, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    EURASIP Journal on Audio, Speech, and Music Processing     page: 000   2013.7

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  274. Objective and subjective evaluation of complementary Wiener filter for speech dereverberation Reviewed

    Kento Ohtani, Tatsuya Komatsu, Kazunobu Kondo, Takanori Nishino, and Kazuya Takeda

    21st International Congress on Acoustics (ICA2013)     page: 00   2013.6

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  275. Stochastic mixture modeling of driving behavior during car following Reviewed

    Pongtep Angkititurakul, Chiyomi Miyajima, and Kazuya Takeda

    Journal of Informatoin and Communication Convergence Engineering   Vol. 11 ( 2 ) page: 95-102   2013.6

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  276. Stochastic mixture modeling of driving behavior during car following Reviewed

    Pongtep Angkititurakul, Chiyomi Miyajima, and Kazuya Taked

    Journal of Informatoin and Communication Convergence Engineering   Vol. 11 ( 2 ) page: 95-102   2013.6

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  277. Stochastic mixture modeling of driving behavior during car following Reviewed

    Pongtep Angkititurakul, Chiyomi Miyajima, and Kazuya Takeda

    Journal of Informatoin and Communication Convergence Engineering     page: 00   2013.6

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  278. Modeling Room Impulse Response via Composites of Spatial-Temporal GP's Reviewed

    Tatsuya Komatsu, Gareth W. Peters, Tomoko Matsui, Ido Nevat, Kazuya Takeda

    ICA 2013 Montreal     page: 00   2013.6

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  279. Computationally efficient single channel dereverberation based on complementary Wiener filter Reviewed

    Kazunobu Kondo, Yu Takahashi, Tatsuya Komatsu, Takanori Nishino, and Kazuya Takeda

    ICASSP2013     page: 00   2013.5

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  280. Modeling head-related transfer functions via spatial-temporal Gaussian process Reviewed

    Tatsuya Komatsu, Takanori Nishino, Gareth Peters, Tomoko Matsui, and Kazuya Takeda

    ICASSP2013     page: 00   2013.5

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  281. Analysis and modeling of entrainment in chorus singing Reviewed

    Motonari Kawagishi, Shota Kawabuchi, Chiyomi Miyajima, Norihide Kitaoka, Kazuya Takeda

    ICASSP2013     page: 00   2013.5

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  282. 楽曲間の類似判定における許容度の推定 Reviewed

    川渕 将太, 宮島 千代美, 北岡 教英, 武田 一哉

    情報処理学会MUS/EC合同研究会   Vol. Vol.2013-MUS-98 ( 2 ) page: 6pages   2013.5

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  283. Estimation of vocal tract parameters for the classification of speech under stress

    Xiao Yao, Takatoshi Jitsuhiro, Chiyomi Miyajima, Norihide Kitaoka, Kazuya Takeda

    2013 IEEE International Conference     page: 00   2013.5

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  284. 楽曲間の類似判断における個人性データの収集とその分析 Reviewed

    川渕将太,宮島千代美,北岡教英,武田一哉,

    情報処理学会論文誌   Vol. 54 ( 4 ) page: 000   2013.4

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  285. Generative approach for robust acoustic model training for blindly separated speech recognition Reviewed

    Norihide Kitaoka, Yuto Dekiura, Kazuya Takeda

    ICA2013/ASA/CAA     page: 00   2013.3

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  286. ばね質量系を利用した合唱における歌声のF0ダイナミクスのモデル化 Reviewed

    川岸 基成, 宮島 千代美, 北岡 教英, 武田 一哉

    情報処理学会MUS/EC合同研究会   Vol. Vol.2013-MUS-98 ( 12 ) page: 6pages   2013.3

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  287. Classification of speech under stress using physical features based on two-mass model Reviewed

    Xiao Yao, Takatoshi Jitsuhiro, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

      Vol. SP2012 ( 128 ) page: 47-52   2013.3

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  288. Spoken document retrieval using combinational use of distances of multiple vector spaces and query expansion with optimized weight parameters Reviewed

    Satoru Tsuge, Hiromasa Ohashi, Norihide Kitaoka, Kazuya Takeda, Kenji Kita

    Proc. NCSP'13     page: 00   2013.3

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  289. 音声対話システムの発話・動作タグN-gramを用いた課題未達成のオンライン検出 Reviewed

    原 直, 北岡教英, 武田一哉

    電子情報通信学会論文誌(D)   Vol. 96-D ( 1 ) page: 81-93   2013.1

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  290. Behavior Signal Processing for Vehicle Applications Reviewed

    Chiyomi Miyajima, Pongtep Angkititrakul, Kazuya Takeda

    APSIPA Transactions on Signal and Information Processing   Vol. 00 ( 00 ) page: 1-13   2013.1

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  291. Modeling and Analysis of Driving Behavior Based on a Probability-Weighted ARX Model Reviewed

    H Okuda, N Ikami, T Suzuki, Y Tazaki, K Takeda

    IEEE Trans. on Intelligent Transportation Systems   Vol. 14 ( 1 ) page: 98-112   2013.1

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  292. CENSREC-2-AV: An evaluation framework for bimodal speech recognition in real environments Reviewed

    Naoya Ukai, Takuya Kawasaki, Satoshi Tamura, Satoru Hayamizu, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    COCOSDA     page: 00   2012.12

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  293. Subjective similarity of music: Data collection for individuality analysis Reviewed

    Naoya Ukai, Takuya Kawasaki, Satoshi Tamura, Satoru Hayamizu, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    APSIPA     page: 00   2012.12

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  294. Self-coaching system based on recorded driving data:Learning from one's experiences Reviewed

    Kazuya Takeda, Chiyomi Miyajima, Tatsuya Suzuki, Pongtep Angkititrakul, Kenji Kurumida, Yuichi Kuroyanagi, Hiroaki Ishikawa, Ryuta Terashima, Toshihiro Wakita, Masato Oikawa, and Yuichi Komada

    IEEE Transactions on Intelligent Transportation systems   Vol. 13   page: 1821-1831   2012.12

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  295. Acoustic model training using feature vectors generated by manipulating speech parameters of real speakers Reviewed

    Tetsuto Kawai, Norihide Kitaoka, Kazuya Takeda

    Proc. APSIPA ASC 2012     page: 00   2012.12

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  296. Acoustic model training using pseudo-speaker feature generated by MLLR transofrmaions for robust speech recognition Reviewed

    Arata Itoh, Sunao Hara, Norihide Kitaoka, Kazuya Takeda

    IEICE Trans. Inf. & Syst   Vol. E95-D ( 10 ) page: 2479-2485   2012.10

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  297. Measuring driver awareness based on correlation between gaze behavior and risks of surrounding vehicles Reviewed

    Masataka Mori, Chiyomi Miyajima, Pongtep Angkititrakul, Takatsugu Hirayama, Yiyang Li, Norihide Kitaoka, and Kazuya Takeda

    ITSC 2012     page: 00   2012.9

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  298. Analysis and prediction of deceleration behavior during car-following using stochastic driver-behavior model Reviewed

    Pongtep Angkititrakul, Chiyomi Miyajima, and Kazuya Takeda

    ITSC 2012     page: 00   2012.9

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  299. Classification of stressed speech using physical parameters derived from two-mass model Reviewed

    Xiao Yao, Takatoshi Jitsuhiro, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    INTERSPEECH 2012     page: 00   2012.9

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  300. Measuring driver awareness based on correlation between gaze behavior and risks of surrounding vehicles Reviewed

    Masataka Mori, Chiyomi Miyajima, Pongtep Angkititrakul, Takatsugu Hirayama, Yiyang li, Norihide Kitaoka, Kazuya Takeda

    ITSC2012     page: 00   2012.9

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  301. Fast source separation based on selection of effective temporal frames Reviewed

    Yusuke Mizuno, Kazunobu Kondo, Takanori Nishino, Norihide Kitaoka, Kazuya Takeda

    Proc. EUSIPCO 2012     page: 00   2012.8

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  302. Impact of driving context on stochastic diver-behavior model: Quantitative analysis of car following task Reviewed

    Pongtep Angkititrakul, Chiyomi Miyajima, and Kazuya Takeda

    2012 IEEE International Conference on Vehicular Electronics and Safety (ICVES 2012)     page: 00   2012.7

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  303. An improved driver-behavior model with combined individual and general driving characteristics Reviewed

    Pongtep Angkititrakul, Chiyomi Miyajima, and Kazuya Takeda

    2012 IEEE Intelligent Vehicles Symposium (IV'12),     page: 00   2012.6

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  304. Causal analysis of task incompletion for spoken dialogs focused on interactions of user and the system Reviewed

    Sunao Hara, Norihide Kitaoka and Kazuya Takeda

    Proc. LREC 2012     page: 00   2012.5

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  305. Data collection for individuality analysis on subjective music similarity evaluation Reviewed

    Shota Kawabuchi, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    The Acoustics 2012     page: 00   2012.5

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  306. Multi-band speech recognition using band-dependent confidence measures of blind source separation Reviewed

    Atsushi Ando, Hiromasa Ohashi, Sunao Hara, Norihide Kitaoka, Kazuya Takeda

    ACOUSTICS 2012     page: 00   2012.5

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  307. Physical characteristics of vocal folds during speech under stress Reviewed

    Xiao Yao, Takatoshi Jitsuhiro, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda,

    ICASSP2012     page: 00   2012.3

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  308. Estimating sound source depth using a small-size array Invited Reviewed

    Satoshi Esaki, Kenta Niwa, Takanori Nishino, and Kazuya Takeda

    ICASSP2012     page: 00   2012.3

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  309. International large-scale vehicle corpora for research on driver behavior on the road Reviewed

    Kazuya Takeda, John Hansen, Pinar Boyraz, Lucas Malta, Chiyomi Miyajima, and Huseyin Abut

    IEEE Transactions on Intelligent Transportation Systems   Vol. 12 ( 4 ) page: 1609-1623   2011.12

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  310. Robust seed model training for speaker adaptation using pseudo-speaker features generated by inverse CMLLR transformation Reviewed

    Arata Itoh, Sunao Hara, Norihide Kitaoka, Kazuya Takeda

    2011 Automatic Speech Recognition and Understanding Workshop (ASRU 2011)     page: 00   2011.12

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  311. Training Robust Acoustic Models Using Features of Pseudo-Speakers Generated by Inverse CMLLR Transformations Reviewed

    Arata Itoh, Sunao Hara, Norihide Kitaoka, Kazuya Takeda

    2011 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2011)     page: 00   2011.10

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  312. Improving driving behavior by allowing drivers to browse their own recorded driving data Reviewed

    Kazuya Takeda, Chiyomi Miyajima, Tatsuya Suzuki, Kenji Kurumida, Yuichi Kuroyanagi, Hiroaki Ishikawa, Pongtep Angkititrakul, Ryuta Terashima, Toshihiro Wakita, Masato Oikawa, and Yuichi Komada

    International IEEE Conference on Intelligent Transportation Systems (ITSC 2011)     page: 00   2011.10

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  313. Behavior signal processing for vehicular applications Reviewed

    Chiyomi Miyajima, Pongtep Angkititrakul, and Kazuya Takeda

    2011 Asia-Pacific Signal and Information Processing Associaton Annual Summit and Conference (APSIPA 2011)     page: 00   2011.10

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  314. Adaptation of driver-behavior model with application to car-following task Reviewed

    Pongtep Angkititrakul, Chiyomi Miyajima, Kazuya Takeda, Ryuta Terashima, and Toshihiro Wakita,

    First International Symposium on Future Active Safety Technology Toward Zero-Traffic-Accident (FAST-zero 2011),     page: 00   2011.9

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  315. CENSREC-4: An evaluation framework for distant-talking speech recognition in reverberant environments Reviewed

    Takahiro Fukumori, Takanobu Nishiura, Masato Nakayama, Yuki Denda, Norihide Kitaoka, Takeshi Yamada, Kazumasa Yamamoto, Satoru Tsuge, Masakiyo Fujimoto, Tetsuya Takiguchi, Chiyomi Miyajima, Satoshi Tamura, Tetsuji Ogawa, Shigeki Matsuda, Shingo Kuroiwa, Kazuya Takeda, and Satoshi Nakamura

    Acoustical Science and Technology   Vol. 32 ( 5 ) page: 201-210   2011.9

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  316. Development and evaluation of Japanese Lombard speech corpus Reviewed

    Tetsuji Ogawa, Takanobu Nishiura, Takeshi Yamada, Norihide Kitaoka, and Tetsunori Kobayashi,

    Inter-noise 2011     page: 00   2011.9

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  317. An analysis of the speech under stress using the two-mass vocal fold model Reviewed

    Xiao Yao, Takatoshi Jitsuhiro, Chiyomi Miyajima, Norihide Kitaoka, Kazuya Takeda

    The 3rd International Workshop on Spoken Dialogue Systems Technology (IWSDS 2011)     page: 00   2011.9

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  318. Efficient blind speech separation suitable for embedded devices Reviewed

    Kazunobu Kondo, Yu Takahashi, Seiichi Hashimoto, Hiroshi Saruwatari, Takanori Nishino, Kazuya Takeda

    19th European signal processing conference (EUSIPCO 2011)     page: 00   2011.9

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  319. On the feasibility of the Mel frequency scale for sound event recognition in realistic conditions Reviewed

    Huy Dat Tran, Yi Ren Leng, Norihide Kitaoka and Haizhou Li

    Inter-noise 2011     page: 00   2011.9

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  320. Adaption of driver-behavior model to car-following tasks Reviewed

    Pongtep Angkititrakul, Chiyomi Miyajima, Kazuya Takeda, Ryuta Terashima, and Toshihiro Wakita,

    First International Symposium on Future Active Safety Technology Toward Zero-Traffic-Accident (FAST-zero 2011)     page: 00   2011.9

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  321. Retrieval systems for recorded driving situations based on measuring similarity between driving behavior signals Reviewed

    Pongtep Angkititrakul, Chiyomi Miyajima, Kazuya Takeda, Ryuta Terashima, and Toshihiro Wakita,

    FAST-zero2011     page: 00   2011.9

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  322. Driving scene retrieval using integrated vehicle motion matching Reviewed

    Yiyang Li, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    5th Biennial Workshop on DSP for In-Vehicle Systems     page: 00   2011.9

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  323. An analysis of the speech under stress using the two-mass vocal fold model Reviewed

    Xiao Yao, Takatoshi Jitsuhiro, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda,

    The 3rd International Workshop on Spoken Dialogue Systems Technology (IWSDS 2011)     page: 00   2011.9

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  324. A driving diagnosis and feedback system for next-generation drive recorders Reviewed

    Chiyomi Miyajima, Kazuya Takeda, Tatsuya Suzuki, Kenji Kurumida, Yuichi Kuroyanagi, Hiroaki Ishikawa, Pongtep Angkititrakul, Ryuta Terashima, Toshihiro Wakita, Masato Oikawa, and Yuichi Komada

    First International Symposium on Future Active Safety Technology Toward Zero-Traffic-Accident (FAST-zero 2011)     page: 00   2011.9

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  325. Efficient blind speech separation suitable for embedded devices Reviewed

    Kazunobu Kondo, Yu Takahashi, Seiichi Hashimoto, Hiroshi Saruwatari, Takanori Nishino, and Kazuya Takeda

    EUSIPCO 2011 (19th European signal processing conference)     page: 00   2011.9

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  326. On-line detection of task incompletion for spoken dialog systems using utterance and behavior tag N-gram vectors Reviewed

    Sunao Hara, Norihide Kitaoka, Kazuya Takeda,

    International Workshop on Spoken Dialog Systems (IWSDS2011)     page: 00   2011.9

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  327. Alternative Frequency Scale Cepstral Coefficient for Robust Sound Event Recognition Reviewed

    Yiren Leng, Huy Dat Tran, Norihide Kitaoka, Haizhou Li,

    Proc. INTERSPEECH2011     page: 00   2011.8

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  328. Detection of task-incomplete dialogs based on utterance-and-behavior tag N-gram for spoken dialog systems Reviewed

    Sunao Hara, Norihide Kitaoka, Kazuya Takeda

    Proc. INTERSPEECH2011     page: 00   2011.8

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    DOI: -

  329. Music Recommendation System Based on Human-to-human Conversation Recognition Reviewed

    Hiromasa Ohashi, Sunao Hara, Norihide Kitaoka, Kazuya Takeda

    2nd International Workshop on Human-Centric Interfaces for Ambient Intelligence (HCIAmI'11)     page: 00   2011.7

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  330. On the use of the two-mass vocal cord model in characterizing the stress speech Reviewed

    Yao Xiao, Takatoshi Jitsuhiro, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda k

    Technical Report of IEICE     page: 00   2011.6

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  331. Detection of distracted driving using a Bayesian network Reviewed

    Hiroaki Ishikawa, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    ICIC Express letters, Part B:Applications, An International journal of Research and Surveys, ICICIC International   Vol. 2 ( 3 ) page: 627-633   2011.6

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  332. Analysis and detection of potentially hazardous situation in real-world driving Reviewed

    Yuichi Kuroyanagi, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    ICICIC Express Letters, PartB:Applications, An Interational Journal of Researxh and Surveys, ICIC International   Vol. 2 ( 3 ) page: 621-626   2011.6

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  333. Modeling and adaptation of stochastic driver-behavior model with application to car following Reviewed

    Pongtep Angkititrakul, Chiyomi Miyajima, and Kazuya Takeda

    2011 IEEE Intelligent Vehicles Symposium     page: 00   2011.6

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  334. Field data collection of a distributed spoken dialog system for music retrieval and its evaluation Reviewed

    Sunao Hara, Norihide Kitaoka, Kazuya Takeda,

    Global Engineering, Science, and Technology society International Transaction on Computer Science and Engineering,   Vol. 64 ( 1 ) page: 33-58   2011.5

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  335. Analysis of real-world driver's frustration Reviewed

    Lucas Malta, Chiyomi Miyajima,Norihide Kitaoka, and Kazuya Takeda,

    IEEE Transactions on Intelligent Transportation Systems   Vol. 12 ( 1 ) page: 109-118   2011.3

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  336. Blind source separation using dodecahedral microphone array under reverberant conditions Reviewed

    Motoki Ogasawara, Takanori Nisino, and Kazuya Takeda

    IEICE TRANSACTIONS on Fundamentalsof Electronics, Communications and Computer   Vol. E94-A ( 3 ) page: 897-906   2011.3

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  337. Improved method of blind speech separation with low computational complexity Reviewed

    Kazunobu Kondo, Yu Takahashi, Seiichi Hashimoto, Hiroshi Saruwatari, Takanori Nishino, and Kazuya Takeda

    Advances in Acoustics and Vibration   Vol. 2011   page: Article ID 765429, 10pages   2011.2

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  338. 音声対話システムの発話系列N-gramを利用した課題未達成対話の検出 Reviewed

    原直、北岡教英、武田一哉

    電子情報通信学会論文誌(D)     page: 00   2011.2

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  339. 行動信号処理の現状と展望 Reviewed

    宮島千代美、武田一哉

    システム制御情報学会誌   Vol. 55 ( 1 ) page: 2-7   2011.1

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  340. Blind source separation using dodecahedral microphone array under reverberant conditions

    Motoki Ogasawara, Takanori Nishino, and Kazuya Takeda

    IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol. 94-A ( 3 ) page: 897-906   2011.1

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  341. 運転行動データベースの構築と応用

    宮島千代美、武田一哉

    システム/制御/情報   Vol. 55   page: 00   2011.1

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  342. Detection of distracted driving using a Bayesian network Reviewed

    Hiroaki Ishikawa,Chiyomi Miyajima,Norihide Kitaoka, and Kazuya Takeda

    2010International Conference on Innovative Computing, Information and Control(ICICIC2010)     page: pp.621-626   2010.12

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  343. Analysis and detection of potentially hazardous situations in real-world driving Reviewed

    Yuichi Kuroyanagi,Chiyomi Miyajima,Norihide Kitaoka, and Kazuya Takeda

    2010International Conference on Innovative Computing, Information and Control(ICICIC2010)451     page: pp.621-626   2010.12

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  344. 自動車運転のマルチモーダル信号収録装置の開発 Reviewed

    尾崎晃、草川高志、西脇由博、マルタ・ルーカス、宮島千代美、西野隆典、北岡教英、伊藤克亘、武田一哉

    電子情報通信学会論文誌(D)   Vol. J93-D ( 5 ) page: 1244-1252   2010.10

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  345. Automatic detection of task-uncompleted dialog for spoken dialog system based on dialog act N-gram Reviewed

    Sunao Hara, Norihide Kitaoka, and Kazuya Takeda

    Proc.INTERSPEECH 2010     page: 3034-3037   2010.9

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  346. CENSREC-1-AV:An audio-visual corpus for noisy bimodal speech recognition Reviewed

    Satoshi Tamura, Chiyomi Miyajima, Norihide Kitaoka, Takeshi Yamada, Satoru Tsuge, Tetsuya Takiguchi, Kazumasa Yamamoto, and Kazuya Takeda

    AVSP2010     page: 00   2010.9

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  347. rapid acoustic model adaption using inverse MLLR-based feature generation Reviewed

    Arata Ito, Sunao Hara, Norihide Kitaoka, and Kazuya Takeda

    International Congress of Acoustics (ICA2010)     page: 942-947   2010.8

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  348. Visualization and dereverberation of head-related transfer function based on spatio-temporal frequency analysis Reviewed

    Yasuko Morimoto, Takanori Nishino, and Kazuya Takeda

    20th International Congress on Acoustics (ICA2010)     page: 00   2010.8

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  349. A Browsing and Retrieval System for Driving Data Reviewed

    Masashi Naito,Chiyomi Miyajima, Takanori Nishino, Norihide Kitaoka, and Kazuya Takeda

    2010 IEEE Intelligent Vehicles symposium (IV'2010)     page: 00   2010.6

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  350. Use of on-road data in evaluating driver performance metrics Reviewed

    Lucas Malta, Akira Ozaki, Chiyomi Miyajima, Norihide Kitaoka, Kazuya Takeda

    SAE International Journal of Passenger Cars Electronic and Electrical Systems     page: 00   2010.5

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  351. Estimation method of user satisfaction using N-gram-based dialog history model for spoken dialog system Reviewed

    Sunao Hara, Norihide Kitaoka, and Kazuya Takeda

    LREC2010     page: 78-83   2010.5

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  352. ANALYZING GRASPING FOR INFERRING COGNITIVE STATES OF USERS Reviewed

    Kotaro Ogino,Takatoshi Jitsuhiro,Chiyomi Miyaijma,Kazuya Takeda

    In Proc.of International Conference on Acoustic Speech and Signal Processing   Vol. 0 ( 0 ) page: 0   2010.3

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  353. A SMALL DODECAHEDRAL MICROPHONE ARRAY FOR BLIND SOURCE SEPARATION Reviewed

    Motoki Ogasawara,Takanori Nishino,Kazuya Takeda

    In proc. of International Conference on Acousitc Speech and Signal Processing   Vol. 0 ( 0 ) page: 0   2010.3

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  354. Analysis of real-world driver's frustration Reviewed

    Lucas Malta, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    IEEE Transactions on Intelligent Transportation Systems   Vol. 12 ( 1 ) page: 109-118   2010.3

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  355. A small dodecahedral microphone array for blind source separation Reviewed

    Motoki Ogasawara, Takanori Nishino, and Kazuya Takeda

    ICASSP2010     page: 00   2010.3

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  356. Acoustic Feature Transformation Based on Discriminant Analysis Preservong Local Structure for Speech Recognition Date of Evaluation Reviewed

    Makoto Sakai, Norihide Kitaoka,Yuya Hattori,Seiichi Nakagawa, and Kazuya Takeda

    IEICE Trans, on Information & Systems   Vol. 000 ( 000 ) page: 000   2010.2

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    DOI: 000

  357. Evaluation of Combinational Use of Discriminant Analysis-based Acoustic Feature Transformation abd Discriminative Training Reviewed

    Makoto SAKAI,Norihide KITAOKA,Yuya HATTORI, Seiichi NAKAGAWA,and Kazuya TAKEDA

    IEICE Trans.on Information & Systems,   Vol. E93-D ( 2 ) page: 395-398   2010.2

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  358. 確率的手法を用いた車線変更軌跡のモデル化 Reviewed

    西脇由博,宮島千代美,北岡教英,武田一哉

    情報処理学会論文誌   Vol. 51 ( 1 ) page: 131-140   2010.1

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  359. Representation and comparison of HRTF in spatio-temporal frequency domain Reviewed

    Yasuko Morimoto, Takanori Nishino, and Kazuya Takeda

    3rd International universal communication symposium(IUCS2009)     page: 00   2009.12

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  360. Driver evaluation based on Classificaton of rapid decelerating patterns Reviewed

    Atsumi Naito,Chiyomi Miyajima,Takanori Nishino,Norihide Kitaoka,Kazuya Takeda

    International Conference on Vehicular Electronics and Safety   Vol. 0 ( 0 ) page: 113-117   2009.11

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  361. A Multimedia Corporus of Driving Behaviors Reviewed

    Lucas Malta,Akira Ozaki,Chiyomi Miyajima,Norihide Kitaoka,Kazuya Takeda

    In proceedings of ISMIR 2009   Vol. 0 ( 0 ) page: 0   2009.11

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  362. Analysis of measured head-related transfer functions based on spatio-temporal frequency characteristic Reviewed

    Yasuko Morimoto,Takanori Nishino,Kazuya Takeda

    In proceedings of IWPASH2009   Vol. 0 ( 0 ) page: 0   2009.11

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  363. Blind Source separation using dodecahedral microphone array for selective listening point audio Reviewed

    Motoki Ogasawara, Takanori Nishino,Kazuya Takeda

    In proceedings of IWPASH 2009   Vol. 0 ( 0 ) page: 0   2009.11

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  364. Evaluation of driver-behavior models in real-world car-following task I Reviewed

    Pongtep Angkititrakul, Ryuta Trashima, Toshihiro Wakita, Chiyomi Miyajima, Kazuya Takeda, and Tatsuya Suzuki

    ICVES2009     page: 00   2009.11

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  365. Analysis of measured head-related tranfer functions based on spatio-temporal frequency characteristics I Reviewed

    Yasuko Morimoto, Takanori Nishino, and Kazuya Takeda

    IWPASH2009     page: 00   2009.11

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  366. Driver evaluation based on the classification of rapid decelerating patterns Reviewed

    Atsumi Naito, Chiyomi Miyajima, Takanori Nishino, Norihide Kitaoka, and Kazuya Takeda

    ICVES2009     page: 00   2009.11

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  367. Blind source separation using dodecahedral microphone array for selective listening point audio Reviewed

    Motoki Ogasawara, Takanori Nishino, and Kazuya Takeda

    IWPASH2009     page: 00   2009.11

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  368. Automatic identification for singing style based on sung melodic contour characterized in phase plane Reviewed

    Tatsuya Kako, Yasunori Ohishi, Hirokazu Kameoka, Kunio Kashino, Kazuya Takeda

    ISMIR 2009, Kobe, Japan, October 26-30, 2009     page: pp.393-397   2009.10

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  369. Prediction Model of Driving Behavior Based on Traffic Conditions and Driver Types Reviewed

    Hideomi Amata,Chiyomi Miyajima,Takanori Nishino,Norihide Kitaoka,Kazuya Takeda

    In Proceedings of ISMIR2009   Vol. 0 ( 0 ) page: 0   2009.10

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  370. AUTOMATIC IDENTIFICATION FOR SINGING STYLE BASED ON SUNG MELODIC CONTOUR CHARACTERIZED IN PHASE PLANE Reviewed

    Tatsuya Kako, Yasunori Ohishi,Hirokazu Kameoka,Kunio Kashino, Kazuya Takeda

    International Conference on Music Information Retrieval (ISMIR2009)     page: 393-397   2009.10

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  371. A stochastic signal model for predicting the vehicle trajectory at lane change Reviewed

    Yoshihiro Nishiwaki, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda

    4th Biennial Workshop on Disgal Signal Processing for In-Vehicles Systems and Safety     page: 00   2009.10

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  372. CENSREC-1-C:An evaluation framework for voice activity detection under noisy environments Reviewed

    Norihide Kitaoka,Takeshi Yamada,Satoru Tsuge,Chiyomi Miyajima,Kazumasa Yamamoto,Takanobu Nishiura,Masato Nakayama,Yuki Denda,Masakiyo Fujimoto,Tetsuya Takiguchi,Satoshi Tamura,Shigeki Matsuda,Tetsuji Ogawa,Shingo Kuroiwa,Kazuya Takeda,Satoshi Nakamura

    Acoustical Science and Technology   Vol. 30 ( 5 ) page: 363-371   2009.9

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  373. Blind source separation based on acoustic pressure distribution and normalized rerative phase using dodecahedral microphone array Reviewed

    Motoki Ogasawara,Takanori Nishino,Kazuya Takeda

    In proceedings of EUSPICO2009   Vol. 0 ( 0 ) page: 1413-1417   2009.8

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  374. Analysis of head-related transfer functions based on spatio-temporal frequency characteristics Reviewed

    Yasuko Morimoto,Takanori Nishino,Kazuya Takeda

    AES TOKYO 2009   Vol. 0 ( 0 ) page: 0   2009.7

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  375. A Study of Driver Behavior Under Potential Threats in Vehicle Traffic Reviewed

    Lucas Malta, Chiyomi Miyajima, Kazuya Takeda

    IEEE Trans. on ITS   Vol. vol.10 ( no.2 ) page: pp.201-210   2009.6

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  376. A Stochastic Modeling of Vehicle and Analysis Reviewed

    Yoshihiro Nishiwaki,Chiyomi Miyajima,Norihide Kitaoka,Kazuya Takeda

    4th Biennial Workshop on Digital Signal Processing   Vol. 0 ( 0 ) page: 0   2009.6

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  377. Multimodel real-world driving data collection and analysis Reviewed

    Luxas Malta,Chiyomi Miyajima,Norihide Kitaoka,Kazuya Takeda

    4th Biennial Workshop on Digital Signal Processing   Vol. 0 ( 0 ) page: 0   2009.6

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  378. Multimodal estimation of a driver's spontaneous irritation Reviewed

    Lucas Malta,Chiyomi Miyajima,Norihide Kitaoka,Kazuya Takeda

    IV2009   Vol. 0 ( 0 ) page: 573-577   2009.6

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  379. Feature transformation based on discriminant analysis preserving local structure for speech recognition Reviewed

    Makoto Sakai, Norihide Kitaoka, Kazuya Takeda

    ICASSP 2009, Taipei, PRC, April 19-24     page: pp.SPE-L3.5   2009.4

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  380. Stochastic modeling of vehicle trajectory during lane-changing Reviewed

    Yoshihiro Nishiwaki, Chiyomi Miyajima, Hidenori Kitaoka, Kazuya Takeda

    ICASSP 2009, Taipei, PRC, April 19-24     page: pp.ITT-P2.8   2009.4

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  381. Spoken dialog stragety based on understanding graph search Reviewed

    Yuji Kinoshita, Chiyomi Miyajima, Norihide Kitaoka, Kazuya Takeda

    ICASSP 2009, Taipei, PRC, April 19-24     page: pp.SLP-P2.3   2009.4

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  382. *Selective Listening Point Audio based on Blind Signal Separation and Stereophonic Technology Reviewed

    Kenta Niwa, Takanori Nishino, Kazuya Takeda

    IEICE Trans. on Infomation and Systems   Vol. vol.E92-D ( no.3 ) page: pp.469-476   2009.3

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  383. DRIVING PROFILE MODELLING AND RECOGNITION BASED ON SOFT COMPUTING APPROACH Reviewed

    Abdul Wahab, Chai Quek, Kazuya Takeda, Chin Tan

    IEEE Transactions on Neural Networks   Vol. vol.20 ( no.4 ) page: pp.563-582   2009.2

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  384. 車載レーザスキャナによる距離データマップの構築と高精度自動車位置推定 Reviewed

    大石康智、後藤真孝、武田一哉

    電子情報通信学会論文誌   Vol. 92-D(2)   page: 215-225   2009.2

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  385. Integrated Speech Enhancement Method using Noise Suppression and Dereverberation Reviewed

    Kenta Niwa, Takanori Nishino, Kazuya Takeda

    IEEE Trans. Audio, Speech, and Language Processing   Vol. 17(2)   page: 231-246   2009.2

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  386. On-Going Data Collection of Driving Behavior Signals, In-Vehicle Corpus and Signal Processing for Driver Behavior, (Book Chapter)

    Chiyomi Miyajima, Takashi Kusawaka, Takanori Nishino, Norihide Kitaoka, Katsunobu Itou, and Kazuya Takeda

    Springer     page: 45-54   2009.1

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  387. Speech dereverberation based on maximum likelihood estimation with time-varying Gaussian source model Reviewed

    IEEE Trans, Audio, Speech, and Language Processing   Vol. 16(8)   page: 1512-1527   2008.11

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  388. 人にやさしい音声インターフェース Reviewed

    鹿野清宏、河原達也、猿渡 洋、武田一哉、河原英紀、徳田恵一、西浦敬信、李 晃伸

    情報処理学会論文誌   Vol. 49 ( 11 ) page: 3789-3797   2008.11

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  389. An integrative recognition method for speech and gestures Reviewed

    Madoka Miki, Chiyomi Miyajima, Takanori Nishino, Norihide Kitaoka, and Kazuya Takeda

    ICMI2008   Vol. - ( - ) page: pp93-96   2008.10

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  390. 3D AV Integrated System Featuring Arbitrary Listening-Point And Viewpoint Generation Reviewed

    Mehrdad Panahpour Tehrani, Kenta Niwa, Norishige Fukushima, Yasushi Hirano, Toshiaki Fujii, Masayuki Tanimoto, Kazuya Takeda, Kenji Mase, Akio Ishikawa, Shigeyuki Sakazawa, Atsushi Koike

    MMSP 2008   ( PID-213 ) page: pp. 855-860   2008.10

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  391. Generating Lane-Change Trajectories of Individual Drivers Reviewed

    Yoshihiro Nishiwaki, Chiyomi Miyajima, Norihide Kitaoka, Ryuta TERASHIMA, Toshihiro Wakita, Kazuya Takeda

    ICVES2008   Vol. - ( - ) page: pp271-275   2008.9

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  392. CENSREC-AV: Evaluation frameworks for audio-visual speech recognition Reviewed

    Satoshi TAMURA, Chiyomi MIYAJIMA, Norihide KITAOKA, Satoru HAYAMIZU, and Kazuya TAKEDA

    AVSP2008   Vol. - ( - ) page: -   2008.9

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  393. CENSREC-4: Development of Evaluation Framework for Distant-talking Speech Recognition under Reverberant Environments Reviewed

    M.Nakayama, Nishiura, Denda, Kitaoka, Yamamoto, Yamada, Tsuge, Miyajima, Fujimoto, Takiguchi, Tamura, Ogawa, Matsuda, Kuroiwa, Takeda, Nakamura

    Interspeech 2008, Brisbane, Australia, September 2008   Vol. - ( - ) page: pp968-971   2008.9

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  394. Parameter Estimation Method of F0 Control Model for Singing Voices Reviewed

    Yasunori Ohishi, Hirokazu Kameoka, Kunio Kashino, Kazuya Takeda

    Interspeech 2008, Brisbane, Australia, September 2008   Vol. - ( - ) page: pp139-142   2008.9

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  395. Building and Combining Document and Music Spaces for Music Query-By-Webpage System Reviewed

    Ryoei Takahashi, Yasunori Ohishi, Norihide Kitaoka, Kazuya Takeda

    Interspeech 2008, Brisbane, Australia, September 2008   Vol. - ( - ) page: pp2020-2023   2008.9

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  396. Binaural sound localization for untrained directions based on a Gaussian mixture model Reviewed

    Takanori Nishino and Kazuya Takeda,

    16th European Signal Processing Conference (EUSIPCO 2008), Lausanne, Switzerland, August 2008   Vol. - ( - ) page: -   2008.8

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  397. 複数モデルの動的選択に基づく気管支枝名自動対応付け手法 Reviewed

    中堂敬司、西野隆典、武田一哉

    電子情報通信学会論文誌(D)   Vol. J91-D(7)   page: 1851-1861   2008.7

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  398. Multi-modal real-world driving data collection, transcription, and integration using Bayesian network, Reviewed

    Lucas Malta, Chiyomi Miyajima, and Kazuya Takeda,

    2008 IEEE Intelligent Vehicles Symposium (IV 2008), Eindhoven, Netherlands   Vol. - ( - ) page: pp150-155   2008.6

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  399. Evaluation Framework for Distant-talking Speech Recognition under Reverberant Environments: newest Part of the CENSREC Series Reviewed

    Takanobu Nishiura, Masato Nakayama, Yuki Denda, Norihide Kitaoka, Kazumasa Yamamoto, Takeshi Yamada, Satoru Tsuge, Chiyomi Miyajima, Masakiyo Fujimoto, Tetsuya Takiguchi, Satoshi Tamura, Shingo Kuroiwa, Kazuya Takeda and Satoshi Nakamura

    LREC2008, May 28-30, Marrakech Morocco     page: 468   2008.5

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  400. In-car Speech Data Collection along with Various Multimodal Signals Reviewed

    Akira Ozaki, Sunao Hara, Takashi Kusakawa, Chiyomi Miyajima, Takanori Nishino, Norihide Kitaoka, Katunobu Itou and Kazuya Takeda

    LREC2008, May 28-30, Marrakech Morocco     page: 472   2008.5

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  401. Multichannel Speech Enhancement Based on Generalized Gamma Prior Distribution with Its Online Adaptive Estimation Reviewed

    Tran HUY DAT, Kazuya TAKEDA, Fumitada ITAKURA

    IEICE TRANSACTIONS on Information and Systems   Vol. E91-D ( 3 ) page: 439-447   2008.3

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  402. Enclding large array signals into a 3D sound field representation for selective listening point audio based on blind source separation, Reviewed

    Kenta Niwa, Takanori Nishino and Kazuya Takeda,

    ICASSP 2008 Las Vegas, USA   Vol. - ( - ) page: pp181-184   2008.3

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  403. Enclding large array signals into a 3D sound field representation for selective listening point audio based on blind source separation Reviewed

    Kenta Niwa, Takanori Nishino and Kazuya Takeda

    ICASSP2008 , Mar.30-Apr.4, Las Vegas, USA     page: pp.181-184   2008.3

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  404. DRIVING PROFILE MODELLING AND RECOGNITION BASED ON SOFT COMPUTING APPROACH Reviewed

    Abdul Wahab, Chai Quek, Kazuya Takeda, Chin Tan

    IEEE Transactions on Neural Networks     page: 000   2008.2

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    DOI: 000

  405. Head-Related Transfer Function measurement in sagittal and frontal coordinates (letter) Reviewed

    Takashi Nakado, Takanori Nishino, Kazuya Takeda

    Acoustical Science and Technology,   Vol. Vol29 ( no.5 ) page: 335-337   2008.2

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  406. Estimation of speaker and listener positions in a car using binaural signals Reviewed

    Madoka Takimoto, Takanori Nishino, Hiroyuki Hoshino and Kazuya Takeda

    Acoustical Science and Technology   Vol. 29 ( 1 ) page: 110-112   2008.1

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  407. 多視点・多聴点データ取得システムを用いた自由視聴点映像生成 Reviewed

    福嶋慶繁, 丹羽健太, 圓道知博, 藤井俊彰, 谷本正幸, 西野隆典, 武田一哉

    電子情報通信学会論文誌   Vol. J91-D ( no.8 ) page: 2039-2041   2008.1

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  408. *相平面に描かれる歌声の基本周波数軌跡:歌唱者の意図する音高目標値系列の推定とハミング検索への応用 Reviewed

    大石 康智, 後藤 真孝, 伊藤 克亘, 武田 一哉

    情報処理学会論文誌   Vol. Vol.49 ( No.11 ) page: pp.3789-3797   2008.1

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    山下記念賞(研究会発表表彰)を受賞した内容をまとめたものである。

  409. Development of VAD evaluation framework CENSREC-1-C and investigation of relationship between VAD and speech recognition performance, Reviewed

    Norihide Kitaoka, Kazumasa Yamamoto, Tomohiro Kusamizu, Seiichi Nakagawa, Takeshi Yamada, Satoru Tsuge, Chiyomi Miyajima, Takanobu Nishiura, Masato Nakayama, Yuki Denda, Masakiyo Fujimoto, Tetsuya Takiguchi, Satoshi Tamura, Shingo Kuroiwa, Kazuya Takeda, and Satoshi Nakamura,

    Proc. IEEE workshop on Automatic Speech Recognition and Understanding (ASRU 2007)   Vol. - ( - ) page: 607-612   2007.12

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  410. Multimodal driving data integration for the analysis of driver's responses to hazardoussituations, Lucas Malta, Chiyomi Miyajima, and Kazuya Takeda, Reviewed

    Lucas Malta, Chiyomi Miyajima, and Kazuya Takeda

    the 1st International Workshop on Tagging, Mining and Retrieval of Human Related Activity Information, Nagoya, Japan   Vol. - ( - ) page: -   2007.11

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  411. 多様な音響環境下における音声認識システム利用時のデータ収集システム Reviewed

    原直,宮島千代美,伊藤克亘,武田一哉

    電子情報通信学会論文誌   Vol. J90-D ( 10 ) page: 2807-2816   2007.10

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  412. 複数の認識器を選択的に用いる音声認識システムのためのスコア補正法 Reviewed

    磯部俊洋,伊藤克亘,武田一哉

    電子情報通信学会論文誌   Vol. J90-D ( 7 ) page: 1773-1780   2007.7

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  413. On-going data collection for driving behavior signal, Reviewed

    Chiyomi Miyajima, Takashi Kusakawa, Takanori Nishino, Norihide Kitaoka, Katsunobu Itou, and Kazuya Takeda

    DSPINCARS 2007   Vol. - ( - ) page: MM-2   2007.6

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  414. Mining potentially hazardous situations in vehicle traffic using driver's reactions, Reviewed

    Lucas Malta, Chiyomi Miyajima, Kazuya Takeda

    proc. of the 2007 IEEE Intelligent Vehicles Symposium   Vol. - ( - ) page: 1144-1149   2007.6

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  415. Generation of Pedal Operation Patterns of Individual Drivers in Car-Following for Personalized Cruise Control Reviewed

    Yoshihiro Nishiwaki, Chiyomi Miyajima, Norihide Kitaoka, Katsunobu Itou, Kazuya Takeda, Kazuya

    proc. of the 2007 IEEE Intelligent Vehicles Symposium   Vol. - ( - ) page: 823-827   2007.6

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  416. Sound localization under conditions of covered ears on the horizontal plane Reviewed

    Madoka Takimoto, Takanori Nishino, Katsunobu Itou and Kazuya Takeda

    Acoustical Science and Technology   Vol. 28 ( 5 ) page: 335-342   2007.5

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  417. スペクトル分析を用いた運転行動信号に含まれる個人性のモデル化 Reviewed

    小澤晃史,西脇由博,脇田敏裕,宮島千代美,伊藤克亘,武田一哉

    小澤晃史,西脇由博,脇田敏裕,宮島千代美,伊藤克亘,武田一哉 電子情報通信学会論文誌   Vol. J90-D ( 4 ) page: 1115-1123   2007.4

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  418. Statistical Segmentation and Recognition of Fingertip Trajectories for a Gesture Interface Reviewed

    Kazuhiro MORIMOTO, Chiyomi MIYAJIMA, Norihide KITAOKA, Katunobu ITOU, Kazuya TAKEDA

    ICMI2007, November 12-15, 2007, Nagoya Japan   Vol. - ( - ) page: 54-57   2007.2

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  419. *Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification Invited Reviewed

    C. Miyajima, Y. Nishiwaki, K. Ozawa, T. Wakita, K. Itou, K. Takeda and F. Itakura

    Proceedings of the IEEE   Vol. 95 ( 2 ) page: 427-437   2007.2

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  420. A Stochastic Representation of the Dynamics of Sung Melody Reviewed

    Yasunori Ohishi, Masataka Goto, Katunobu Itou, Kazuya Takeda

    ISMIR 2007, September 23rd-27th, Wienna, Austria   Vol. - ( - ) page: -   2007.1

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  421. A Virtual Button Interface Using Fingertip Movements Reviewed

    Kazuhiro Morimoto, Chiyomi Miyajima, Kazuya Takeda

    ICMLC, 19-22 August 2007, Hong Kong, China   Vol. - ( - ) page: 2089-2093   2007.1

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  422. 楽曲検索システムにおけるプレイリストに適応した音響モデル構築手法に関する検討

    原直,宮島千代美,伊藤克亘,北岡教英,武田一哉

    情報処理学会研究報告   Vol. Vol. 2007 ( No.136 SLP-67-16 ) page: 87-90   2007.1

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  423. Estimation of HRTFs on the horizontal plane using physical features Reviewed

    Takanori Nishino, Naoya Inoue, Kazuya Takeda and Fumitada Itakura

    Applied Acoustics   Vol. Vol.68 ( issue8 ) page: 897-908   2007.1

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  424. 両耳間音圧差の包楽を用いたガウス分布モデルに基づく音源方向推定 Reviewed

    西野隆典、井上直哉、伊藤克亘、武田一哉

    日本音響学会誌   Vol. 63 ( 1 ) page: 3-12   2007.1

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  425. Rubust in-car speech recognition based on nonlinear multiple regression Reviewed

    Weifeng Li, Kazuya Takeda, Fumitada Itakura

    EURASHIP JOURNAL on Advance in Signal Processing   Vol. 2007 ( Article ID 16921 ) page: 1-10   2007.1

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  426. CENSREC-3:An Evaluation Framework for Japanese Speech Recognition in Real Car-Driving Environments

    Masakiyo Fujimoto, Kazuya Takeda, Satoshi Nakamura

    IEICE Trans, Inf. And Syst.,   Vol. E89-D ( 11 ) page: 2783-2793   2006.11

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  427. On line Gaussian mixture modeling in the log-power domain for signal-to-noise ratio estimation and speech enhancement Reviewed

    Tran Huy Dat, Kazuya Takeda, Satoshi Itakura

    Speech Recognition   Vol. 48   page: Issue 11   2006.11

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  428. 指先の動きを利用した仮想ボタン入力インターフェースの検討 Reviewed

    森本一広、宮島千代美、伊藤克亘、武田一哉

    2006年情報科学技術レターズ   Vol. LK-013   page: 305-308   2006.9

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  429. スペクトル包絡と基本周波数の時間変化を利用した歌声と朗読音声の識別 Reviewed

    大石康智、後藤真孝、伊藤克亘、武田一哉

    情報処理学会論文誌   Vol. 47 ( 6 ) page: 1822-1830   2006.6

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  430. Maximum a Posterior Probability and Cumulative Distribution Function Methods for Speech Xpectral Estimation with Application in Noise Suppression Filtering

    Tran Huy Dat, Kazuya Takeda, Fumitada Itakura

    Lecture Notes in Computer Science   Vol. 3817   page: 328-337   2006.2

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  431. ADAPTIVE REGRESSION BASED FRAMEWORK FOR IN-CAR SPEECH RECOGNITION, Reviewed

    Weifeng Li, Katsunobu Itou, Kazuya Takeda

    ICASSP2006, Toulouse, May 2006     page: SLP-P5.2   2006.1

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  432. Single-Channel Multiple Regression for In-Car Spee

    Weifeng LI,Katsunobu ITOU,Kazuya TAKEDA,Fumitada ITAKURA

    IEICE Trans. on Inf. & Syst   Vol. VOL.E89-D   page: 1032-1039   2006.1

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  433. Robust In-car Speech Recognition Based On Nonlinear Multiple Regression

    Weifeng LI,Kazuya Takeda,Fumitada Itakura

    EURASIP Journal on Advances in Signal Processing   Vol. Volume 2007 ( Article ID 16921 ) page: 1-10   2006.1

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  434. MULTICHANNEL SPEECH ENHANCEMENT BASED ON SPEECH SPECTRAL MAGNITUDE ESTIMATION USING GENERALIZED GAMMA PRIOR DISTRIBUTION, Reviewed

    Tran Huy Dat, Kazuya Takeda, Fumitada Itakura

    ICASSP2006, Toulouse, May 2006     page: SAM-P6.3   2006.1

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  435. ARBITRARY LISTENING-POINT GENERATION USING SUB-BAND REPRESENTATION OF SOUND WAVE RAY-SPACE, Reviewed

    Mehrdad Panahpour Tehrani, Yasushi Hirano, Toshiaki Fujii, Shoji Kajita, Kazuya Takeda, Kenji Mase

    Mehrdad Panahpour Tehrani, Yasushi Hirano, Toshiaki Fujii, Shoji Kajita, Kazuya Takeda, Kenji Mase     page: MMSP-P3.11   2006.1

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  436. Characterizing in-car Conversational Speech of Different Dialogue Modes, Reviewed

    Hiroshi Fujimura, Chiyomi Miyajima, Nobuo Kawaguchi, Katsunobu Itou, Kazuya Takeda and Fumitada Itakura

    ICICIC 2006, Beijing, August-September     page: pp.552-556   2006.1

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  437. MULTIPOINT MEASURING SYSTEM FOR VIDEO AND SOUND - 100-camera and microphone system -, Reviewed

    Toshiaki Fujii, Kensaku Mori, Kazuya Takeda, Kenji Mase, Masayuki Tanimoto, Yasuhito Suenaga

    ICME, Toronto, July 2006     page: MA2-P4   2006.1

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  438. 両音間音圧差の特徴量分布をガウス分析近似した音源方向推定モデルの検討

    西野隆典,武田一哉

    音講論集・日本音響学会(2006年秋季研究発表会)   ( 37263 ) page: 469-470   2006.1

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  439. 運転操作信号のケプストラム分析に基づく運転者識別

    武田 一哉,小澤 晃史,西脇 由博,脇田 敏裕,宮島 千代美, 伊藤 克亘

    情報処理学会   Vol. 2006-SLP-60   page: 19-24   2006.1

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  440. Statistical Analysis for Thesaurus Construction using an Encuclopedic Corpus

    Yasunori Ohishi,Katunobu Itoh,Kazuya Takeda,Atsushi Fujii

    5th International conference on Language Resources     page: 1368-1371   2006.1

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  441. Development of Micro-Dodecahedral Loudspeakerfor Measuring Head-Related Transfer Functions In The Proximal Region

    Seiichiro Hosoe,Takanori Nishino,Katunobu Itoh,Kazuya Takeda

    Proc.ICASSP   Vol. ICASSP 2006 ( VOL.5 ) page: AE-P6.5-329   2006.1

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  442. Cepstral Analysis of Driving Behavioral Signals for Driver Identification

    Chiyomi Miyajima,Yoshihiro Nishiwaki,Koji Ozawa,Toshihiro Wakita,Katunobu Itoh, Kazuya Takeda

    Proceedings of 2006 IEEE International Conference   Vol. VOL.5   page: 921-924   2006.1

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  443. Measurement of Head Related Transfer Functions with Micro-Dodecahedral Loudspeaker in the Proximal Region

    Takanori Nishino,Seiichiro Hosoe,Katunobu Itoh,Kazuya Takeda

    Proc.WESPAC   Vol. WESPAC IX ( 2006 ) page: 397   2006.1

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  444. On Human Capability and Acoustic Cues for Discriminating Singing and Speaking Voices

    Yasunori Ohishi,Masataka Goto,Katunobu Itoh,Kazuya Takeda

    9th International Conference on Music Percerption     page: 1381-1387   2006.1

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  445. Gamma Modeling of Speech Power and Its Online Estimation for Statistical Speech Enhancement Reviewed

    Tran Huy Dat, Kazuya Takeda, Fumitada Itakura

    IEICE Trans. Inf. and Syst.,   Vol. E89-D ( 3 ) page: 1040-1049   2006.1

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  446. Driver Identification Using Driving Signals Reviewed

    Toshiyuki Wakita, Chiyomi Miyajima, Katsunobu Itou, and Kazuya Takeda

    IEICE trans, Inf.& Syst.,   Vol. E89-D ( 3 ) page: 1188-1194   2006.1

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  447. 給電指令電話の音声検索システム Reviewed

    瀬川修、武田一哉

    電気学会論文誌C   Vol. 125-C ( 9 ) page: 1438-1443   2005.9

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  448. The Sound Wave Ray-Space Reviewed

    M. P. Tehrani, Y. Hirano, T. Fujii, S. Kajita, K. Takeda, M. Tanimoto, K. Mase

    ICME 2005, Amsterdam, July 2005   Vol. - ( - ) page: -   2005.7

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  449. CIAIR In-Car Speech Corpus - Influence of the Driving Status(letter)

    Nobuo Kawaguchi, Shigeki Matubara, Kazuya Takeda, and Fumitada Itakura

    IEICE-D(E)   Vol. E88-D ( 3 ) page: 578-582   2005.3

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  450. AURORA-2J: An Evaluation Framework for Japanese Noisy Speech Recogniton

    Satoshi Nakamura, Kazuya Takeda, Kazumasa Yamamoto, Takeshi Yamada, Shingo Kuroiwa, Norihide Kitaoka, Takanobu Nishiura, Akira Sasou, Mitsunori Mizumachi, Chiyomi Miyajima, Masakiyo Fujimoto, and Toshiki Endo

    IEICE-D(E)   Vol. E88-D ( 3 ) page: 384-390   2005.3

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  451. Analysis and Recognition of Whispered Speech

    Taisuke Ito, Kazuya Takeda, ando Fumitada Itakura

    Speech Communication   Vol. 45 ( 2 ) page: 139-152   2005.2

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  452. Speaker verification using Gaussian mixture models within changing real car environments Reviewed

    Xianxian Zhang, John Hansen, Pongtep Angkititrakul, Kazuya Takeda

    INTERSPEECH2005, Lisboa, Portugal   Vol. - ( - ) page: -   2005.1

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  453. Modeling of individualities in driving through spectral analysis of behavioral signals Reviewed

    Koji Ozawa, Toshihiro Wakita, Chiyomi Miyajima, Katsunobu Itou, Kazuya Takeda

    ISSPA'2005 Sydney, Australia   Vol. - ( - ) page: -   2005.1

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  454. Speech Enhancement based on SNR-Dependent Empirical Statistical Estimation in Log-Spectral Magnitude domain Reviewed

    Tran Huy Dat, Kazuya Takeda and Fumitada Itakura

    International Workshop on Acoustic Echo and Noise Control   Vol. - ( - ) page: -   2005.1

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  455. Subjective and Objective Quality Assessment of Regression-enhanced Speech in Real Car Environments Reviewed

    Li Wifent, Katsunobu Itou, Kazuya Takeda, Fumitada Itakura

    INTERSPEECH2005, Lisboa, Portugal   Vol. - ( - ) page: -   2005.1

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  456. Improved Noise Estimation and Log-spectral Regression for In-car Speech Recongnition

    Weifeng LI,Katunobu ITOU,Kazuya TAKEDA

    ICDEW 2005     page: 1206   2005.1

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  457. 音声対話インタフェースの長期利用時における学習効果の評価

    原直,白勢彩子,宮島千代美,伊藤克亘,武田一哉

      ( 2005-SLP-55(4) ) page: 17-22   2005.1

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  458. 実走行車内単語音声データベースCENSREC-3と共通評価環境の構築

    藤本雅清,中村 哲,武田一哉 黒岩 眞吾,山田 武志,北岡教英,山本一公,水町光徳,西浦敬信,佐宗晃

      ( 2005-SLP-55(8) ) page: 41-46   2005.1

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  459. SPATIAL CODING BASED ON THE EXTRACTION OF MOVING SOUND SOURCES IN WAVEFIELD SYNTHESIS Reviewed

    Toshiyuki KIMURA,Kazuhiko KAKEHI,Kazuya TAKEDA,Fumitada ITAKURA

    ICASSP 2005   Vol. Vol.3   page: Ⅲ-293-Ⅲ-296   2005.1

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  460. GENERALIZED GAMMA MODELING OF SPEECH AND ITS ONLINE ESTIMATION FOR SPEECH ENHANCEMENT

    Tran Huy DAT,Kazuya TAKEDA,Fumitada ITAKURA

    ICASSP 2005   Vol. Vol.4   page: Ⅳ-181-Ⅳ-184   2005.1

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  461. SNR AND LOCAL NOISE POWER ESTIMATIONS BASED ON GAUSSIAN MIXTURE MODELING ON THE LOG-POWER DOMAIN

    Kazuya TAKEDA,Tran Huy DAT,Hiroshi FUJIMURA,Fumitada ITAKURA

    ICASSP 2005   Vol. Vol.1   page: Ⅰ-881-Ⅰ-884   2005.1

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  462. ANALYSIS OF A LARGE IN-CAR SPEECH CORPUS AND ITS APPLICATION TO THE MUTIMODEL ASR

    Hirosi FUJIMURA,Chiyomi MIYAJIMA,Katsunobu ITOU,Kazuya TAKEDA,Fumitada ITAKURA

    ICASSP 2005   Vol. Vol.1   page: I-445-I-448   2005.1

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  463. TWO-STAGE NOISE SPECTRA ESTIMATION AND REGRESSION BASED IN-CAR SPEECH RECOGNITION USING SINGLE DISTANT MICROPHONE

    Weifeng Li,Katunobu Itou,Kazuya Takeda,Fumitada Itakura

    ICASSP 2005   Vol. Vol.1   page: I-533-I-536   2005.1

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  464. Speech enhancement based on MAP-log spectral magnitude estimation using the gamma prior of the speech power

    Tran Huy DAT,Kazuya TAKEDA,Fumitada ITAKURA

    NSIP 2005     page: 43   2005.1

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  465. MAP and cumulative distribution function equalization methods for the speech spectral estimation with application in noise suppression filtering

    Tran Huy DAT,Kazuya TAKEDA,Fumitada ITAKURA

    NOLISP 2005     page: 259-268   2005.1

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  466. A speech enhancement system based on data clusterin and cumulative histogram equalization

    Tran Huy DAT,Kazuya TAKEDA,Fumitada ITAKURA

    ICDEW 2005     page: 1207   2005.1

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  467. 波面合成におけるチャネル数の主観的影響 -音源が正面付近にある場合-

    木村敏幸,筧一彦,武田一哉,板倉文忠

    日本バーチャルリアリティ学会 論文誌   Vol. TVRSJ Vol.10 ( 2 ) page: 257-266   2005.1

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  468. Environmental Warping for In-car Speech Recognition

    Weifeng LI,Katunobu ITOU,Kazuya TAKEDA,Fumitada ITAKURA

    NSIP2005     page: 35   2005.1

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  469. Sound field auralizaion system in free listening positions

    Toshiyuki KIMURA,Wataru MIZUNO,Takanori NISHINO,Kazuya TAKEDA

    Forum Acusticum 2005     page: 2511-2516   2005.1

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  470. HRTF modeling using physical features

    Naoya INOUE,Takanori NISHINO,Katsunobu ITOU,Kazuya TAKEDA

    Forum Acusticum 2005     page: L199-L202   2005.1

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  471. Measurement of head-related transfer functions in the proximal region

    Seiichiro HOSOE,Takanori NISHINO,Katunobu ITOU,Kazuya TAKEDA

    Forum Acusticum 2005     page: 2539-2542   2005.1

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  472. Evaluation of sound localization under condition of covered ears

    Madoka TAKIMOTO,Takanori NISHINO,Katunobu ITOU,Kazuya TAKEDA

    Forum Acusticum 2005     page: L203-L206   2005.1

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  473. Modeling method of a room impulse response with cepstrum analysis

    Takanori NISHINO,Fuminori SAITO,Katunobu ITOU,Kazuya TAKEDA

    Forum Acusticum 2005     page: 1887-1890   2005.1

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  474. Data Collection and Evaluation of Speech Recognition for Motorbike Riders

    Hirosi TANAKA,Hirosi FUJIMURA,Chiyomi MIYAJIMA,Takanori NISHINO,Katunobu ITOU, Kazuya TAKEDA

    INTERSPEECH 2005     page: 2665-2668   2005.1

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  475. Discrimination between Singing and Speaking Voices

    Yasunori OHISHI,Masataka GOTO,Katunobu ITO,Kazuya TAKEDA

    INTERSPEECH2005     page: 1141-1144   2005.1

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  476. Driver identification based on spectral analysis of driving behavioral signals

    Yoshihiro NISHIWAKI,Koji OZAWA,Toshihiro WAKITA,Chiyomi MIYAJIMA,Katunobu ITOU, Kazuya TAKEDA

    DSP in Cars 2005     page: M1-6   2005.1

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  477. Parametric Versus Non-Parametric Models of Driving Behavior Signals for Driver Identification

    Toshihiro WAKITA,Koji OZAWA,Chiyomi MIYAJIMA,Kazuya TAKEDA

    AVBPA2005   Vol. LNCS3546   page: 739-747   2005.1

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  478. Driver Identification Using Driving Behavior Signals

    Toshihiro WAKITA,Koji OZAWA,Chiyomi MIYAJIMA,Kei IGARASHI,Katunobu ITOU, Kazuya TAKEDA

    ITSC2005   Vol. Vol.E89-D ( No.3 ) page: 1188-1194   2005.1

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  479. 運転行動を用いたドライバ識別

    脇田敏裕,小澤晃史,宮島千代美,五十嵐圭,伊藤克亘, 武田一哉

    自動車技術会学術講演会前刷集   Vol. No.119-05   page: 17-20   2005.1

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  480. Evaluation of HRTFs estimated using physical features

    Naoya INOUE,Toshiyuki KIMURA,Takanori NISHINO,Katsunobu ITOU,Kazuya TAKEDA

    Acoustical Science and Technology   Vol. Vol.26 ( No. 5 ) page: 453-455   2005.1

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  481. The present status progress and usage of speech databases in Japan Reviewed

    Hisao Kuwabara,Shuichi Itahashi,Mikio Yamamoto,Satoshi Nakamura,Toshiyuki Takezawa, Kazuya Takeda

    Acoustical Science and Technology   Vol. 26 ( 1 ) page: 62-66   2005.1

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  482. 移動音源がある音場の空間符号化ー音源抽出による伝送量の削減ー

    木村敏幸,筧一彦,武田一哉,板倉文忠

    日本バーチャルリアリティ学会 論文誌   Vol. TVRSJ Vol.10   page: 101-109   2005.1

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  483. Multiple Regression of Log Spectra for In-Car Speech Recognition Using Multiple Distributed Microphones

    Weifeng LI,Tetsuya SHINDE,Hiroshi FUJIMURA,Chiyomi MIYAJIMA,Takanori NISHINO, Katunobu ITOU,Kazuya TAKEDA,Fumitada ITAKURA

    IEICE Trans   Vol. Vol.E88-D ( No.3 ) page: 834-390   2005.1

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  484. Construction and Evaluation of a Large In-Car Speech Corpus

    Kazuya TAKEDA,Hiroshi FUJIMURA,Katunobu ITOU,Nobuo KAWAGUCHI,Shigeki MATSUBARA, Fumitada ITAKURA

    IEICE Trans.   Vol. Vol.E88-D ( No.3 ) page: 553-561   2005.1

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  485. Speech Recognition Using Finger Tapping Timings

    Hirmitsu BAN,Chiyomi MIYAJIMA,Katunobu ITOU,Kazuya TAKEDA,Fumitada ITAKURA

    IEICE Trans.   Vol. Vol.E88-D ( No.3 ) page: 667-670   2005.1

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  486. ケプストラム分析を用いた実収録運転行動信号に含まれる個人性のモデル化(レター)

    西脇由博、小澤晃史、宮島千代美、伊藤克亘、武田一哉

    情報科学技術レターズ   Vol. LL-007   page: 289-292   2005.1

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  487. Adaptive Log-spectral Regression for In-Car Speech Recognition using Multiple Distributed Microphones(letter)

    Weifeng Li, Kazuya Takeda, and Fumitada Itakura

    IEEE Signal Processing Letters   Vol. 12 ( 4 ) page: 340-343   2005.1

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  488. Adaptive Nonlinear Regression Using Multiple Distributed Microphones for In-Car Speech Recognition

    Weifeng Li, Chiyomi Miyajima, Takanori Nishino,Katunobu Itou, Kazuya Takeda, and Fumitada Itakura

    IEICE-A(E)   Vol. E88-A ( 7 ) page: 1716   2005.1

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  489. Speech recognition using synchronization between speech and figre tapping Reviewed

    H. Bann, C.Miyajima, K.Itou, K.Takeda, F.Itakura

    INTERSPEECH/ICSLP 2004, Cheju Korea, November 2004   Vol. - ( - ) page: -   2004.11

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  490. Example-based Spoken Dialogue System with Online Example Augmentation Reviewed

    H.Murao, N. Kawaguchi, S. Matsubara, Y. Yamaguchi, K. Takeda and Y. Inagaki

    INTERSPEECH/ICSLP 2004, Cheju Korea, November 2004     page: FrA1502p.15   2004.11

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  491. Optimizing Regression for in-car Speech Recognition using Multiple Distributed Microphones Reviewed

    W. Li, K. Takeda and F. Itakura

    INTERSPEECH/ICSLP 2004, Cheju Korea, November 2004     page: FrA1502p.15   2004.11

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  492. Recent Progress of Open-Source LVCSR Engine Julius and Japanese Model Repository Reviewed

    T.Kawahara, A.Lee, K.Takeda, K.Itou and K.Shikano

    INTERSPEECH/ICSLP 2004, Cheju Korea, November 2004     page: Spec4402p.6   2004.11

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  493. Audio-Visual Speaker Localization for Car Navigation Systems Reviewed

    X.Zhang, K.Takeda, J.Hansen and T.Maeno

    INTERSPEECH/ICSLP 2004, Cheju Korea, November 2004     page: Spec3603p.4   2004.11

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  494. CIAIR In-Car Speech Database Reviewed

    N.Kawaguchi, S.Matsubara, Y.Yamaguchi, K.Takeda and F. Itakura

    INTERSPEECH/ICSLP 2004, Cheju Korea, November 2004     page: FrA2702p.18   2004.11

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  495. Analysis of In-car speech recognition experiments using a large-scale multi-mode dialogue corpus Reviewed

    K.Fujimura, K.Itou, K.Takeda,F.Itakura

    INTERSPEECH/ICSLP 2004, Cheju Korea, November 2004     page: Spec4001o.2   2004.11

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  496. AURORA-2J: Japanese speech data collection for performance evaluation of speech recognition in noise Reviewed

    Satoshi Nakamura, Kazumasa Yamamoto, Kazuya Takeda,Shingo Kuroiwa, Norihide Kitaoka,Takeshi Yamada,Mitsunori Mizumachi, Takanobu Nishiura, Masakiyo Fujimoto, Akira Saso, Toshiki Endo

    International Conference on Speech and Language Technology/Oriental-COCOSDA   Vol. - ( - ) page: -   2004.1

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  497. An Advanced Japanese Speech Corpus for In-car Spoken Dialogue Research, Reviewed

    Yuki Irie, Nobuo Kawaguchi, Shigeki Matsubara, Itsuki Kishida, Yukiko Yamaguchi, Kazuya Takeda, Fumitada Itakura, and Yasuyoshi Inagaki

    O-COCOSDA 2004     page: SDC-2   2004.1

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  498. Robust SNR estimation of noisy speech based on Gaussian mixtures modeling on log-power domain Reviewed

    Tran Huy Dat, Kazuya Takeda, Fumitada Itakura

    COST278 and ISCA Tutorial and Research Workshop (ITRW) on Robustness Issues in Conversational Interaction   Vol. - ( - ) page: -   2004.1

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  499. Dialouge characteristics in different communication modes, Reviewed

    Katsunobu Itou, Kouji Fujimura, Nobuo Kawaguchi, Kazuya Takeda, and Fumitada Itakura

    Special Workshop in Maui Lectures by Masters in Speech Processing   Vol. - ( - ) page: -   2004.1

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  500. In-Car Spoken Dialogue Corpus and Its Application, Reviewed

    Nobuo Kawaguchi, Shigeki Matsubara, Hiroya Murao, Itsuki Kishida, Yuki Irie, Yukiko Yamaguchi, Kazuya Takeda and Fumitada Itakura

    Special Workshop in Maui Lectures by Masters in Speech Processing   Vol. - ( - ) page: -   2004.1

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  501. Biometric Identification Using Driving Behavioral Signals Reviewed

    Kei Igarashi, Chiyomi Miyajima, Katsunobu Itou, Kazuya Takeda, Fumitada Itakura and Huseyin Abut

    ICME'2004   Vol. - ( - ) page: -   2004.1

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  502. Method for determining sound localization Acoustical Science and Technology by auditory masking

    Kazuhiro UCHIDA,Takanori NISHINO,Kazuya TAKEDA,Fumitada ITAKURA

    Acoustical Science and Technology   Vol. 25 ( 6 ) page: 480-482   2004.1

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  503. DSP for In-Vehicle and Mobile Systems

    Huseyin ABUT,John HANSEN,Kazuya TAKEDA(eds.)

    Springer Publisher   Vol. -   page: 000   2004.1

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    DOI: 000

  504. Measurement of the Head Related Transfer Function using the Spark Noise

    Takanori NISHINO,Seiichiro HOSOE,Kazuya TAKEDA,Fumitada ITAKURA

    ICA2004   ( Tu5.D.1 ) page: Ⅱ-1437-Ⅱ-1438   2004.1

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  505. In-car speech recognition experiments using a large-scale multi-mode dialogue corpus

    Hiroshi FUJIMURA,Katsunobu ITOU,Kazuya TAKEDA,Fumitada ITAKURA

    ICA2004   ( Th2.H.1 ) page: Ⅳ-2583-Ⅳ-2586   2004.1

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  506. Subjective assessments for the effect of the number od channel signals on the sound field reproduction used in wavefield synthesis

    Toshiyuki KIMURA,Kazuhiko KAKEHI,Kazuya TAKEDA,Fumitada ITAKURA

    ICA2004   ( Th.P1.17 ) page: Ⅳ-3159-Ⅳ-3162   2004.1

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  507. Biometric Identification Using Driving Behamitoral Signals

    Kei IGARASHI,Chiyomi MIYAJIMA,Katsunobu ITOU,Kazuya Takeda,Fumitada ITAKURA, Huseyin ABUT

    ICME2004   Vol. Vol.1   page: 65-68   2004.1

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  508. 音声情報処理の観点から見た室内音場の評価について

    武田一哉,小村道昭,清水泰博,梶田将司,板倉文忠

    建築音響研究会資料   ( AA2004-24 ) page: 1月6日   2004.1

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  509. Multimedia Corpus of In-Car Speech Communication

    Nobuo KAWAGUCHI,Kazuya TAKEDA,Fumitada ITAKURA

    Journal of VLSI Signal Processing   Vol. 36   page: 153-159   2004.1

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  510. 事典コーパスを用いた単語階層関係の統計的解析

    大石康智,伊藤克亘,武田一哉,藤井敦,板倉文忠

      ( LF-001 ) page: 75-78   2004.1

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  511. 運転行動信号に含まれる個人性に関する検討

    小澤晃史,伊藤克亘,武田一哉,脇田敏裕,板倉文忠

      ( LK-004 ) page: 247-250   2004.1

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  512. Audio-Visual Speaker Localization for Car Navigation Systems

    Xianxian ZHANG,Kazuya TAKEDA,John H. L. HANSEN,Toshiki MAENO

    ICSLP04   ( Spec3603p.4 ) page: 2501-2504   2004.1

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  513. Analysis of In-car speech recognition experiments using a larger-scale multi-mode dialogue corpus

    Hiroshi FUJIMURA,Katsunobu ITOU,Kazuya TAKEDA,Fumitada ITAKURA

    ICSLP04   ( Spec4001p.2 ) page: 2313-2316   2004.1

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  514. RECENT PROGRESS OF OPEN-SOURCE LVCSR ENGINE JULIUS AND JAPANESE MODEL REPOSITORY -SOFTWARE OF CONTINUOUS SPEECH RECOGNITION CONSOURTIUM-

    Tatsuya KAWAHARA,Akinobu LEE,Kazuya TAKEDA,Katsunobu ITOU,Kiyohiro SHIKANO

    ICSLP04   ( Spec4402p.6 ) page: 3069-3072   2004.1

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    Language:English  

  515. Example-based Spoken Dialogue System with Online Example Augmentation

    Hiroya MURAO,Nobuo KAWAGUCHI,Shigeki MATSUBARA,Yukiko YAMAGUCHI,Kazuya TAKEDA, Yasuyoshi INAGAKI

    ICSLP04   ( Spec4402p.7 ) page: 3073-3076   2004.1

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  516. Optimizing Regression for in-car Speech Recognition using Multiple Distributed Microphones

    Weifeng LI,Kazuya TAKEDA,Fumitada ITAKURA

    ICSLP04   ( FrA1502P.15 ) page: 2689-2692   2004.1

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  517. Speech enhancement based on magnitude estimation using the Gamma prior

    Tran Huy DAT,Weifeng LI,Kazuya TAKEDA,Fumitada ITAKURA

    ICSLP04   ( FrA1502p.16 ) page: 2693-2696   2004.1

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  518. SPEECH RECOGNITION USING SYNCHRONIZATION BETWEEN SPEECH AND FINGER TAPPING

    Hiromitu BAN,Chiyomi MIYAJIMA,Katsunobu ITOU,Kazuya TAKEDA,Fumitada ITAKURA

    ICSLP04   ( ThC2501lo.2 ) page: 2289-2292   2004.1

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  519. CIAIR In-Car Speech Database

    Nobuo KAWAGUCHI,Shigeki MATSUBARA,Yukiko YAMAGUCHI,Kazuya TAKEDA,Fumitada ITAKURA

    ICSLP04   ( FrA2702p.18 ) page: 2789-2792   2004.1

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  520. 音声対話による楽曲検索システム

    原直,白勢彩子,宮島千代美,伊藤克亘,武田一哉

      ( 2004-SLP-53(6) ) page: 81-86   2004.1

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  521. スパーク音源を用いた頭部伝達関数の測定

    荒木潤二,西野隆典,武田一哉,板倉文忠

    日本音響学会誌   Vol. 60 ( 6 ) page: 314-318   2004.1

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  522. 自動車の中での音声認識

    武田一哉

    情報処理   Vol. 45 ( 10 ) page: 1038-1043   2004.1

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  523. Data Collection and Evaluation of AURORA-2 Japanese Corpus Reviewed

    Satoshi Nakamura, Kazumasa Yamamoto, Kazuya Takeda, Shingo Kuroiwa,, Norihide Kitaoka, Takeshi Yamada, Mitsunori Mizumachi, Takanobu Nishiura, Masakiyo Fujimoto, Akira Saso, Toshiki Endo

    ASRU2003   Vol. - ( - ) page: -   2003.12

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  524. IN-CAR SPEECH RECOGNITION USING DISTRIBUTED MICROPHONES - ADAPTING TO AUTOMATICALLY DETECTED DRIVING CONDITIONS - Reviewed

    Hideki Banno, Tetsuya Shinde, Kazuya Takeda and Fumitada Itakura

    Hideki Banno, Tetsuya Shinde, Kazuya Takeda and Fumitada Itakura     page: I324-I327   2003.5

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  525. Construction and analysis of the multi-layered in-car spoken dialogue corpus, Reviewed

    Nobuo Kawaguchi, Shigeki Matsubara, Itsuki Kishida, Yuki Irie, Yukiko Yamaguchi, Kazuya Takeda, Fumitada Itakura

    DSP in mobile, April, 2003, Nagoya   Vol. - ( - ) page: -   2003.4

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  526. In-car speech recognition using distributed microphones Reviewed

    Tetsuya Shinde, Kazuya Takeda, Fumitada Itakura

    DSP in mobile, April, 2003, Nagoya   Vol. - ( - ) page: -   2003.4

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  527. Is our driving behavior unique? Reviewed

    Kei Igarashi, Kazuya Takeda, Fumitada Itakura, Huseyin Abut

    DSP in mobile, April, 2003, Nagoya   Vol. - ( - ) page: -   2003.4

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  528. A Study on Domain Recognition of Spoken Dialogue Systems Reviewed

    T. Isobe, S. Hayakawa, H. Murao, T. Mizutani, K. Takeda, F. Itakura

    Eurospeech'03, Geneva     page: pp.1889-1892   2002.9

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  529. Experiments on Recognition of Lavalier Microphone Speech and Whispered Speech in Real World Environments, Reviewed

    K. Tatara, T. Ito, P. Zolfaghari, K. Takeda & F. Itakura

    ICSLP'02, Sep., 2002, Denver     page: pp.653-656   2002.9

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  530. Integration of Noise Reduction Algorithms for Aurora2 Task Reviewed

    Takeshi Yamada, Jiro Okada, Kazuya Takeda, Norihide Kitaoka, Masakiyo Fujimoto, Shingo Kuroiwa, Kazumasa Yamamoto, Takanobu Nishiura, Mitsunori Mizumachi, Satoshi Nakamura

    Eurospeech'03, Geneva     page: pp.1769-1772   2002.9

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  531. Acoustical analysis and Recognition of Whispered Speech Reviewed

    Taisuke Itoh, Kazuya Takeda and Fumitada Itakura

    ICASSP 2002   Vol. - ( - ) page: -   2002.5

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  532. SYNTHESIS OF CAR NOISE BASED ON A COMPOSITION OF ENGINE NOISE AND FRICTION NOISE Reviewed

    Yoshihide Ban, Hideki Banno, Kazuya Takeda and Fumitada Itakura

    ICASSP 2002   Vol. - ( - ) page: -   2002.5

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  533. Recognition of Consonant-Vowel (CV) Units of Speech in a Broadcase News Corpus Using Support Vector Machines Reviewed

    C.Chandra Sekhar, Kazuya Takeda and Fumitada Itakura

    SVM2002, LNCS 2388     page: pp.171-185   2002.1

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  534. Acoustical analysis and Recognition of Whispered Speech Reviewed

    Taisuke Itoh, Kazuya Takeda and Fumitada Itakura

    ASRU 2001, Dec., 2001   Vol. - ( - ) page: -   2001.12

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  535. Robust speech recognition based on selective use of missing frequency band HMMs Reviewed

    Y. Kawamura, K. Takeda, F. Itakura

    Eurospeech'01, Sep., 2001, Aalborg     page: pp.1115-1118   2001.9

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  536. Multimedia data collection of in-car speech communication Reviewed

    N.Kawaguchi, N.Matsubara, K.Takeda, F.Itakura, Y.Inagaki

    Eurospeech'01, Sep., 2001, Aalborg     page: pp.2027-2030   2001.9

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  537. Continuous speech recognition without end-point detection Reviewed

    O.Segawa, K. Takeda, F. Itakura ?

    ICASSP2001, May, 2001, Salt Lake City     page: pp.245-248   2001.5

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  538. A Study on perceptual distance measure for phase spectrum of stimuli Reviewed

    H. Banno, K. Takeda, F. Itakura ?

    ICASSP2001, May, 2001, Salt Lake City     page: pp.3297-3300   2001.5

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  539. Blind source separation combining frequency-domain ICA and beam forming Reviewed

    H. Saruwatari, K. Takeda, K.Shikano ?

    ICASSP2001, May, 2001, Salt Lake City     page: pp.2733-2736   2001.5

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  540. Direction of arrival estimation based on nonlinear microphone array Reviewed

    H. Saruwatari, H.Kamiyanagida, K. Takeda, F. Itakura, K.Shikano

    ICASSP2001, May, 2001, Salt Lake City     page: pp.3033-3036   2001.5

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  541. Close-class-set discrimination method for recognitionof stop-sonsonant-vowel utterances using Support Vector Machines, Reviewed

    Sechar CC, Takeda K, Itakura F

    ARTIFICAL NEURAL NETWORKS-ICANN 2001, PROCEEDINGS LECTURE NOTES IN COMPUTER SCIENCE 2130     page: 399-404   2001.1

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  542. 水平方向及び仰角方向に関する頭部伝達関数の補間 Reviewed

    西野隆典,梶田将司,武田一哉,板倉文忠

    日本音響学会誌   Vol. - ( - ) page: -   2001.1

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  543. Robust speech recognition based on selective use of missing frequency band HMMs

    Y. Kawamura, K. Takeda, F. Itakura

    Proc. of seventh European Conference on Speech Communication and techonology, pp.1115-1118 (Eurospeech'01, Sep., 2001, Aalborg)     page: 1115-1118   2001.1

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  544. 日本語ディクテーション基本ソフトウエア(99年度版) Reviewed

    河原達也,李晃伸,小林哲則,武田一哉,峯松信明,嵯峨山茂樹,伊藤克亘, 伊藤彰則,山本幹男,山田篤,宇津呂武仁,鹿野清宏

    日本音響学会誌   Vol. 57 ( 3 ) page: 210-214   2001.1

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  545. Direction of Arrival Estimation Using Nonlinear Microphone Array Reviewed

    H.Kamiyanagida, H. Saruwatari, K. Takeda, F. Itakura, and K. Shikano

    IEICE Trans. Fundamentals   Vol. E84-A ( 4 ) page: 000   2001.1

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    DOI: 000

  546. WEBベースコースウエアのための音声入力システムの開発 Reviewed

    西村竜一,梶田将司,武田一哉,板倉文忠,鹿野清宏

    情報処理学会論文誌   Vol. 23 ( 3 ) page: 605-613   2001.1

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  547. 車内音声対話収集システムの開発 Reviewed

    河口信夫,岩博之,牛窪誠一,武田一哉,稲垣康善,板倉文忠

    電子情報通信学会論文誌,DII, Vol. J84.DII, No.6, pp.909-916   Vol. J84-DII ( 6 ) page: 903-916   2001.1

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  548. The effect of group delay spectrum on timbre Reviewed

    Hideki Banno, Kazuya Takeda and Fumitada Itakura

    Acoustical Science and Technology   Vol. - ( - ) page: -   2001.1

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  549. Blind Source Separation based on Subband ICA and Beamforming Reviewed

    H.Saruwatari, S.Kurita, K.Takeda, F.Itakura and K.Shikano

    ICSLP2000, Nov. 2000, Beijin     page: pp.633-636?   2000.11

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  550. Free Software Toolkit for Japanese Large Vocabulary Continuous Speech Recognition Reviewed

    T.Kawahara, A.Lee, T.Kobayashi, K.Takeda el al

    ICSLP2000, Nov. 2000, Beijin     page: T.Kawahara, A.Lee, T.Kobayashi, K.Takeda el al   2000.11

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  551. Vector Space Representation of Language Probabilities through SVD of N-gram Matrix Reviewed

    S.Terashima, K.Takeda and F.Itakura

    ICSLP2000, Nov. 2000, Beijin     page: pp.633-636?   2000.11

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  552. Construction of Speech Corpus in Moving Car Environment Reviewed

    N.Kawaguchi, S.Matsubara, H.Iwa, S.Kajita, K.Takeda, F.Itakura and Y.Inagaki

    ICSLP2000, Nov. 2000, Beijin     page: pp.1281-1284   2000.11

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  553. AN ACOUSTIC MEASURE FOR PREDICTING RECOGNITION PERFORMANCE DEGRADATION Reviewed

    pp.3297-3300

    ICASSP2000, June, 2000, Istanbul     page: pp.1739-1742   2000.6

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  554. Evaluation of Blind Signal Separation Method Using Directivity Pattern Under Reverberant Conditions Reviewed

    S.Kurita, H. Saruwatari, S. Kajita, K. Takeda, F. Itakura

    ICASSP2000, June, 2000, Istanbul     page: pp.3140-3143   2000.6

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  555. Speech Enhancement Using Nonlinear Microphone Array with Noise Adaptive Complementary Beamforming Reviewed

    H. Saruwatari, S. Kajita, K. Takeda, F. Itakura

    ICASSP2000, June, 2000, Istanbul     page: pp.1049-1052   2000.6

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  556. Speech Recognition Based on Space Diversity Using Distributed Multi-Microphone Reviewed

    Y. Shimizu, S. Kajita, K. Takeda, F. Itakura

    ICASSP2000, June, 2000, Istanbul     page: pp.1747-1750   2000.6

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  557. A New Phonetic Tied-Mixture Model for Efficient Decoding Reviewed

    A. Lee, T. Kawahara, K. Takeda, K. Shikano?

    ICASSP2000, June, 2000, Istanbul     page: pp.1269-1272   2000.6

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  558. 重回帰分析に基づく頭部伝達特性の推定 Reviewed

    西野隆典,中井勇佑,武田一哉,板倉文忠

    電子情報通信学会論文誌   Vol. J84-A ( 3 ) page: 260-268   2000.1

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  559. 文部省COEプログラム統合音響情報研究拠点

    武田一哉・板倉文忠

    日本音響学会誌   Vol. 56 ( 11 ) page: 000   2000.1

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    DOI: 000

  560. どうすれば,データ共有を成功させることができるか

    伊藤克亘・河原達也・武田一哉

    情報処理,Vol.41, No.7 (2000.7) pp.781-786   Vol. 41 ( 7 ) page: 781-786   2000.1

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  561. マルチメディア情報処理(解説記事) (特集、映像情報メディア年報) Reviewed

    春日正男・山内結子・岡崎彰男夫・武田一哉・林伸二

    映像情報メディア学会誌   Vol. 54 ( 7 ) page: 984-994   2000.1

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  562. どうすれば,データ共有を成功させることができるか(解説記事) (特集、ここまできた自然言語処理ー例文の収集とその利用ー) Reviewed

    伊藤克亘・河原達也・武田一哉

    情報処理   Vol. 41 ( 7 ) page: 781-786   2000.1

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  563. 日本語ディクテーション基本ソフトウエア(98年度版) Reviewed

    河原達也 李晃伸 小林哲則 武田一哉 峯松信明 伊藤克亘 伊藤彰則 山本幹男 山田篤 宇津呂武仁 鹿野清宏

    日本音響学会誌(技術報告)   Vol. 56 ( 4 ) page: 255-259   2000.1

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  564. Japanese Dictation Toolkit-1998version

    kazuya takeda

    The Journal of the Acoustical Society of Japan   Vol. 56 ( 4 ) page: 255-259   2000.1

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  565. Phonetic Tied-Mixture モデルを用いた大語彙連続音声認識 Reviewed

    李晃伸,河原達也,武田一哉,鹿野清宏

    電子情報通信学会論文誌, J83-DII, No.12, pp.2517--2525(2000.12)   Vol. J83-DII ( 12 ) page: 2517-2525   2000.1

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    音素内の分布要素を共有することで、精密な音素の音響モデルを作成しつつ、高速に認識に利用可能な音響モデルを提案している。

  566. バンドエリミネーションを用いたオーディオ信号へのデータハイディンング Reviewed

    池田幹男,豊島亮蔵,武田一哉,板倉文忠

    電子情報通信学会論文誌   Vol. J38-DII ( 11 ) page: 2350-2359   2000.1

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  567. 側抑制性重みづけを用いた雑音環境下におけるSTRAIGHT分析合成系の品質改善 Reviewed

    戸田智基,坂野秀樹,梶田将司,武田一哉,板倉文忠,鹿野清宏

    電子情報通信学会論文誌   Vol. J38-DII ( 11 ) page: 2180-2189   2000.1

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  568. 空間音響特性を考慮したスペースダイバシチ型音声認識 Reviewed

    清水泰博,梶田将司,武田一哉,板倉文忠

    電子情報通信学会論文誌   Vol. J38-DII ( 11 ) page: 2448-2456   2000.1

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  569. SVDを用いたN-gram確率の線形空間表現 Reviewed

    寺島志郎,武田一哉,板倉文忠

    電子情報通信学会論文誌   Vol. J38-DII ( 11 ) page: 2388-2396   2000.1

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  570. A Waveform Measure For Predicting Recognition PerformanceDegradation Reviewed

    M.Kondo, K.Takeda and F.Itakura

    ASRU'99, Dec, 1999, Keystone     page: pp.I-27   1999.12

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  571. Japanese Dictation Toolkit: Plug-and-play Framework For Speech Recognition R&D Reviewed

    T.Kawahara, T.Kobayashi, K.Takeda, N.Minematsu, K.Itou, M.Yamamoto, A.Yamada, T.Utsuro, K.Shikano

    ASRU'99, Dec, 1999, Keystone     page: pp.I-393   1999.12

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  572. 事前に他人受理誤り率を指定する話者照合方式 Reviewed

    早川昭二 武田一哉 板倉文忠

    電子情報通信学会論文誌   Vol. J82-DII ( 12 ) page: 2212-2220   1999.12

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  573. Speech enhancement using nonlinear microphone array under nonstationary noise conditions Reviewed

    H.Saruwatari, S.Kajita,K.Takeda and F.Itakura

    Eurospeech'99, Sep., 1999, Budapest     page: pp.2567-2570   1999.9

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  574. Voice conversion through nonlinear warping of STRAIGHT spectrum Reviewed

    N.Maeda, H.Banno, S.Kajita, K.Takeda and F.Itakura

    Eurospeech'99, Sep., 1999, Budapest     page: pp.827-830   1999.9

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  575. JNAS:Japanese speech corpus for large vocabulary continuous speech recognition research Reviewed

    Katunobu ITO,Mikio YAMAMOTO,Kazuya TAKEDA,Tosiyuki TAKEZAWA Tatsuo MATSUOKA,Tetsunori KOBAYASHI,Kiyohiro SHIKANO and Sshuichi ITAHASHI

    Juronal of Acoustic Society Japan(E)   Vol. 20 ( 3 ) page: 119-206   1999.5

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  576. Compensating of Room Acoustic Transfer Functions Affected by Change of Room Temperature Reviewed

    M.Omura, M.Yada, H.Saruwatari, S.Kajita, K.Takeda and F.Itakura

    ICASSP'99, Mar, 1999, Phoenix   Vol. - ( - ) page: -   1999.3

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  577. Speech Enhancement Using Nonlinear Microphone Array with Complementary Beamforming Reviewed

    H.Saruwatari, S.Kajita, K.Takeda and F.Itakura

    ICASSP'99, Mar, 1999, Phoenix   Vol. - ( - ) page: -   1999.3

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  578. 長さ毎に用意されたセグメント標準パターンとの照合に基づく音声認識 Reviewed

    池田卓史,梶田将司,武田一哉,板倉文忠

    電子情報通信学会論文誌, (研究速報)   Vol. J82-DII ( 2 ) page: 308-311   1999.1

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  579. Japanese speech corpus for large vocabulary continuous speech recognition research

    kazuya takeda

    The Journal of the Acoustical Society of Japan   Vol. 20 ( 3 ) page: 199-206   1999.1

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  580. Speech Enhancement Using Nonlinear Microphone Array Based on Complementary Beamforming Reviewed

    H. Saruwatari, S. Kajita, K. Takeda, and F. Itakura

    IEICE Trans.Fundamentals   Vol. E82-A ( 8 ) page: 000   1999.1

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 000

  581. 事前に他人受理誤り率を指定する話者照合方式 Reviewed

    早川昭二,武田一哉,板倉文忠

    電子情報通信学会誌文誌   Vol. J82-DII ( 12 ) page: 2212-2220   1999.1

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  582. 日本語ディクテーション基本ソフトウェア(97年度版) Reviewed

    河原達也,李晃伸,小林哲則,武田一哉,峯松信明,伊藤克亘, 伊藤彰則,山本幹男,山田篤,宇津呂武仁,鹿野清宏

    日本音響学会誌 (技術報告)   Vol. 20 ( 3 ) page: 233-2239   1999.1

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  583. 水平面上の頭部伝達関数の補間 Reviewed

    西野隆典,梶田将司,武田一哉,板倉文忠

    日本音響学会誌   Vol. 55 ( 2 ) page: 91-99   1999.1

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  584. Estimating entropy of a language from optimal word insertion penalty Reviewed

    K.Takeda, A.Ogawa and F.Itakura

    ICSLP'98, Nov., 1998, Sydney     page: pp.2095-2098   1998.11

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  585. The Design of the Newspaper-Based Japanese Large Vocabulary Continuous Speech Recognition corpus Reviewed

    K.Itou, M.Yamamoto, K.Takeda, K.Takezawa, T.Matsuoka, K.Kobayashi, K.Shikano

    ICSLP'98, Nov., 1998, Sydney     page: pp.3261-3264   1998.11

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  586. Sharable Software Repository for Japanese Large Vocabulary Continuous Speech Recognition Reviewed

    Recognition T.Kawahara, T.Kobayashi, K.Takeda, N.Minematsu, K.Itou, M.Yamamoto, A.Yamada, T.Utsuro, K.Shikano

    ICSLP'98, Nov., 1998, Sydney     page: pp.3257-3260   1998.11

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  587. Balancing Acoustic and Linguistic Probabilities Reviewed

    A.Ogawa, K.Takeda and F.Itakura

    ICASSP'98, May, 1998, Seatle     page: Vol.I pp.181-184   1998.5

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  588. Spectral Weighting of SBCOR for Noise Robust Speech Recognition. Reviewed

    S.Kajita, K.Takeda and F.Itakura

    ICASSP'98, May, 1998, Seatle     page: pp.621-624   1998.5

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    Language:English  

  589. Design and development of Japanese speech corpus for large vocabulary continuous speech recognition. Reviewed

    K.Itou, K.Takeda, T.Takezawa, T.Matsuoka, K.Shikano, T.Kobayashi and S.Itahashi

    Oriental COCOSDA   Vol. - ( - ) page: -   1998.1

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  590. Common platform of Japanese large vocabulary continuous speech recognizer assessment -proposal and initial results -. Reviewed

    T.Kawahara, A.Lee, T.Kobayashi, K.Takeda, N.Minematsu, K.Itou, A.Itou, M.Yamamoto, A.Yamada, T.Utsuro and K.Shikano

    Oriental COCOSDA   Vol. - ( - ) page: -   1998.1

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  591. 包絡と音源の独立操作による音声モーフィング Reviewed

    坂野秀樹,武田一哉,鹿野清宏,板倉文忠

    電子情報通信学会論文誌   Vol. J81-DII ( 9 ) page: 1360-1367   1998.1

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  592. 第3回欧州音声会議(会議報告) Reviewed

    小林隆夫・山下洋一・中村哲・阿部匡伸・小森康弘・武田一哉

    日本音響学会誌   Vol. 54 ( 2 ) page: 883-888   1998.1

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  593. Blind Signal Separation for Recognizing Overlapped Speech Reviewed

    T.Taniguti, S.Kajita, K.Takeda, and F.Itakura

    The Journal of the Acoustical Society of Japan   Vol. 19 ( 6 ) page: 385-390   1998.1

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  594. Noise Robust Speech Recognition using Sub-band Cross-Correlation Analysis Reviewed

    Sshouji Kajita, Kazuya Takeda, and Fumitada Itakura

    IEICE Transactions on Information and Systems.   Vol. E81-D ( 10 ) page: 1079-1086   1998.1

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  595. 一般化ベルヌーイ試行に基づく言語確率の補正方法 Reviewed

    小川厚徳,武田一哉,板倉文忠

    電子情報通信学会論文誌   Vol. J81-DII ( 12 ) page: 2703-2711   1998.1

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  596. 中心周波数の逆数の整数倍の相関を用いた帯域分割自己相関分析 Reviewed

    梶田将司,武田一哉,板倉文忠

    日本音響学会誌   Vol. 54 ( 2 ) page: 111-118   1998.1

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  597. Balancing stochastic knowledge on acoustics and linguistics. Reviewed

    K.Takeda, A.Ogawa and F.Itakura

    SSS'97     page: pp.133--138   1997.12

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  598. Language Modeling for Robust Balancing of Acoustic and Lingustic Probabilities Reviewed

    A.Ogawa, K.Takeda and F.Itakura

    ASRU-97, Santa Barbara     page: pp.246--253   1997.12

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  599. Applying Blind Signal Separation to the Recognition of Overlapped Speech Reviewed

    T.Taniguchi, S.Kajita, K.Takeda and F.Itakura

    Eurospeech'97, September, 1997, Rhodes   Vol. vol.2   page: pp.1103-1107   1997.9

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  600. Speech Morphing by Progressive Interpolation of Spectra Reviewed

    H.Banno, S.Kajita, K.Takeda, K.Shikano, F.Itakura

    ICSP'97, Seoul   Vol. vol.1   page: pp.149--153   1997.8

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  601. A Language Model Based on Generalized Bernoulli Traials Reviewed

    A.Ogawa, K.Takeda, F.Itakura

    ICSP'97, Seoul   Vol. vol.2   page: pp.765--770   1997.8

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  602. Speaker Identification Using Harmonic Structure of LP-residual Spectrum Reviewed

    S.Hayakawa, K.Takeda, F.Itakura

    EFFACES     page: pp.253--260   1997.3

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  603. A Binaural Speech Processing Method Using Subband-Crosscorrelation Analysis for Noise Robust Recognition Reviewed

    S.Kajita, K.Takeda, F.Itakura

    ICASSP'97   Vol. vol.2   page: pp.1243-1246   1997.1

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  604. 種々の定常雑音下におけるLombard音声の認識法の検討 Reviewed

    若尾淳,武田一哉, 板倉文忠

    電子情報通信学会論文誌   Vol. J80-DII ( 7 ) page: 1643-1650   1997.1

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  605. 音源分離による音声認識性能の改善 Reviewed

    武田一哉・板倉文忠

    日本音響学会誌   Vol. 53 ( 11 ) page: 883-888   1997.1

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  606. ヒューマンスピーチライフノイズに含まれる音声的特徴の検討 Reviewed

    梶田将司,小林大祐,武田一哉,板倉文忠

    日本音響学会誌   Vol. 53 ( 5 ) page: 337-345   1997.1

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  607. 複数の発声様式を用いた話者モデルの学習法の検討 Reviewed

    後藤雅彦,早川昭二,武田一哉,板倉文忠

    電子情報通信学会論文誌DII   Vol. J80-DII ( 1 ) page: 10月17日   1997.1

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  608. A Speech Detection Method Using Likelihood of Partial Sentence Hypothesis for Continuous Speech Recognition

    The Transactions of the Institute of Electronics, Information and Communication Engineers DII   Vol. J80-DII ( 11 ) page: 2895-2903   1997.1

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  609. 線形予測残差スペクトルの調波構造に含まれる個人性情報を用いた話者 認識 Reviewed

    早川昭二,武田一哉, 板倉文忠

    電子情報通信学会論文誌   Vol. J80-A ( 9 ) page: 1360-1650   1997.1

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  610. Feature Space Reduction through Nonlinear Identity Mapping Reviewed

    H.Ito, S.Kajita, K.Takeda, F.Itakura

    ASJ-ASA Third Joint Meeting   Vol. 4aSC4   page: pp.2756   1996.12

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  611. On the Use of Zero-Crossing Analysis for Multi-Channel Signal Processing Reviewed

    T.Sugihara, S.Kajita, K.Takeda, F.Itakura

    ASJ-ASA Third Joint Meeting   Vol. 1aSP6   page: pp.2576   1996.12

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  612. Interpolating HRTF for Auditory Virtual Reality Reviewed

    T.Nishino, S.Mase, S.Kajita, K.Takeda, F.Itakura

    ASJ-ASA Third Joint Meeting   Vol. 1pSP6   page: pp.2602   1996.12

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  613. On the Problems in Applying Bell's Blind Separation to Real Environments Reviewed

    T.Taniguchi, H.Yehia, S.Kajita, K.Takeda, F.Itakura

    ASJ-ASA Third Joint Meeting   Vol. 1pSP4   page: pp.2602   1996.12

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  614. Variability of Lombard Effects under Different Noise Csnditions Reviewed

    A.Wakao, K.Takeda, F.Itakura

    ICSLP'96, Philladelphia     page: pp.2009-2012   1996.10

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  615. Extracting Speech Features from Human Speech-like Noise Reviewed

    D.Kobayashi, S.Kajita, K.Takeda, F.Itakura

    ICSLP'96, Philladelphia     page: pp.418-421   1996.10

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  616. Subband-Crosscorrelation Analysis for Robust Speech Recognition Reviewed

    S.Kajita, K.Takeda, F.Itakura

    ICSLP'96, Philladelphia     page: pp.422-425   1996.10

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  617. 大語彙連続音声認識用新聞記事読み上げコーパス

    武田一哉

    人文学と情報処理   Vol. 12   page: 80-85   1996.1

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  618. An Acoustically Oriented vocal-Tract Model Reviewed

    Hani C. Yahia, Kazuya Takeda and Fumitada Itakura

    IEICE Transactions on Information and Systems.   Vol. E79-D ( 8 ) page: 1198-1208   1996.1

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  619. Nベスト意味探索と再評価法を用いた大規模内線受付装置の試作 Reviewed

    黒岩眞吾,内藤正樹,武田一哉,谷戸文広,山本誠一,

    電子情報通信学会論文誌   Vol. J79-DII ( 12 ) page: 2132-2138   1996.1

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  620. A Prototype of a Realtime Japanese-Korean Speech Translation System Reviewed

    M.Suzuki, N.Inoue, K.Takeda, F.Yato, S.Yamamoto

    EUROSPEECH, Madrid     page: pp.1951-1954   1995.9

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  621. Voice-Activated Telephone Extension System for 5,000 Branch Phones Reviewed

    S.Yamamoto, K.Takeda, M.Naito, S.Kuroiwa

    AVIOS'95, San Jose     page: pp.123-129   1995.9

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  622. Intelligent Network Services using Speech Recognition and Its Field Trailas Reviewed

    S.Yamamoto, K.Takeda, N.Inoue, S.Kuroiwa

    TELECOM 95   Vol. - ( - ) page: -   1995.9

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  623. Top-down Speech Detection and NBest Meaning Search in a Voice Activated Telephone Extension System Reviewed

    K.Takeda, S.Kuroiwa, M.Naito, S.Yamamoto

    EUROSPEECH, Madrid     page: pp.1075-1078   1995.9

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  624. Error Analysis of Field Trial Result of a Spoken Dialogue Systems for Telecommunications Reviewed

    Shingo Kuroiwa, Masaki Naito, Naomi Inoue, Seiichi Yamamoto

    IEICE Transactions onInformation and Systems.   Vol. E78D ( 6 ) page: 636-641   1995.1

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  625. 音声研究の現状と課題 Reviewed

    粕谷秀樹・渡辺隆夫・杉山雅英・小林隆夫・阿部匡伸・武田一哉

    日本音響学会誌   Vol. 51 ( 8 ) page: 618-620   1995.1

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  626. ヒューマンスピーチライク雑音における音声的特徴の分析 Reviewed

    小林大祐, 梶田将司, 武田一哉, 板倉文忠

    信学技報   Vol. - ( - ) page: -   1995.1

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  627. 音声の高域を用いた発声内容独立型話者認識 Reviewed

    早川昭二, 武田一哉, 板倉文忠

    信学技報   Vol. - ( - ) page: -   1995.1

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  628. A vocal-tract area function trajectory representation oriented to the speech production inverse problem Reviewed

    Hani Yehia, Kazuya TAKEDA, Fumitada ITAKURA

    Annual Meeting of ASJ   Vol. - ( - ) page: -   1995.1

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  629. 話者識別システムの発声様式の変動に対する頑健性について Reviewed

    後藤雅彦, 武田一哉, 板倉文忠

    信学技報   Vol. - ( - ) page: -   1995.1

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  630. 異なる雑音環境下で発声されたLombard音声の正規化 Reviewed

    若尾淳, 武田一哉, 板倉文忠

    信学技報   Vol. - ( - ) page: -   1995.1

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  631. レベル交差時間情報を用いた音声信号の特徴抽出 Reviewed

    杉原貴明, 梶田将司, 武田一哉, 板倉文忠

    東海連大   Vol. - ( - ) page: -   1995.1

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  632. 話者の発声様式の相違と話者識別の関係の検討 Reviewed

    後藤雅彦, 武田一哉, 板倉文忠

    東海連大   Vol. - ( - ) page: -   1995.1

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  633. 砂時計型ニューラルネットによる音声スペクトルの次元圧縮 Reviewed

    伊藤博紀, 武田一哉, 板倉文忠

    東海連大   Vol. - ( - ) page: -   1995.1

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  634. Optimal Choice Forcusing Matrices for Microphone Array Processing Reviewed

    Zheng Liu, Kazuya Takeda and Humitada Itakura

    Tokai Resional Joint Meeting of Electronics Related Societys   Vol. - ( - ) page: -   1995.1

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  635. 2チャンネル信号間の相互相関に基づいたSBCOR分析 Reviewed

    梶田将司, 武田一哉, 板倉文忠

    東海連大   Vol. - ( - ) page: -   1995.1

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  636. lind Separation法の有効性の検討 Reviewed

    谷口友彦, Hani Yehia, 武田一哉, 板倉文忠

    東海連大   Vol. - ( - ) page: -   1995.1

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  637. ヒューマンスピーチライク雑音の分析 Reviewed

    小林大祐, 梶田将司, 武田一哉, 板倉文忠

    東海連大   Vol. - ( - ) page: -   1995.1

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  638. 行列によるトレリス計算を用いたHMMの文レベルでの識別学習 Reviewed

    村上哲範, 武田一哉, 河井恒, 山本誠一

    信学技報   Vol. - ( - ) page: -   1995.1

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  639. A Voice-Activated Telephone Exchange System and Its Field Trial Reviewed

    S.Yamamoto, K.Takeda, N.Inoue, S.Kuroiwa, M.Naito

    IVTTA 94, Kyoto     page: pp.21-26   1994.9

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  640. A Trellis Based Implementation of Discriminative Trainig Reviewed

    T.Murakami, S.Kuroiwa, K.Takeda, S.Yamamoto

    ICSLP'94, Yokohama     page: pp.299-302   1994.9

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  641. 電話音声の連続音声認識に基づく内線電話受け付け装置の試作と評価

    武田一哉

    電子情報通信学会誌   Vol. J77-A ( 2 ) page: 223-231   1994.1

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  642. Speaker verification using Gaussian mixture models within changing real car environments

    Xianxian Zhang, John Hansen, Pongtep Angkititrakul, Kazuya Takeda

    Journal of theAcoustic Society of Japan(E)   Vol. 15   page: 87-96   1994.1

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  643. 連続音声認識に基づく内線電話受付け装置の試作と評価(共著) Reviewed

    黒岩眞吾 武田一哉 井ノ上直己 野垣内出 山本誠一他

    電子情報通信学会文誌   Vol. J77A ( 2 ) page: 223-231   1994.1

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  644. ガーベジHMMを用いた自由発話文中の不要語処理法(共著) Reviewed

    井ノ上直己, 武田一哉, 山本誠一

    電子情報通信学会論文誌   Vol. J77A ( 2 ) page: 215-222   1994.1

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  645. A Real Time IsolatedWord Recognizer for Telephone Input

    kazuya takeda

    Journal of theAcoustic Society of Japan(E)   Vol. 15   page: 87-96   1994.1

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  646. Online Collection of Spontaneous Speech Using a Voice Activated Telephone Exchanger. Reviewed

    S.Kuroiwa, K.Takeda. N.Inoue, I.Nogaito, S.Yamamoto

    ISSD'93, Tokyo     page: pp.25-28   1993.11

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  647. Improving Robustness of Network Grammar by Using Class HMM Reviewed

    K.Takeda, N.Inoue, S.Kuroiwa, T.Konuma, S.Yamamoto

    European Conference on Speech Communication Technology, Berlin   Vol. Vol.3   page: pp.1623-1626   1993.10

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  648. A Voice Activated Extension Telephone Exchange System Reviewed

    S.Kuroiwa, K.Takeda, N.Inoue, I.Nogaito, S.Yamamoto

    European Conference on Speech Communication and Technology, Berlin   Vol. Vol.3   page: pp.1793-1796   1993.9

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  649. 内線電話接続受け付け装置のための連続音声認識方式 Reviewed

    武田一哉, 黒岩眞吾, 井ノ上直己, 山本誠一

    KDD R&D 150     page: 39-46   1993.1

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  650. 言語情報を利用した母音継続時間長の制御(共著) Reviewed

    海木佳延,武田一哉,匂坂芳典

    電子情報通信学会論文誌   Vol. J75(A) ( 3 ) page: 467-473   1993.1

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  651. Implementation and Evaluation of an Extension Number Guidance System Utlizing Telephone Dialogue Reviewed

    S.Kuroiwa,K.Takeda,F.Yato,S.Yamamoto,K.Owa,M.Shouzakai,R.Matsuomoto

    IVTTA '92, New Jurgy     page: pp.5-9   1992.10

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  652. Architecture and Algorithms of a Real-time Word Recognizer for Telephone Input Reviewed

    S.Kuroiwa, K.Takeda, F.Yato, S.Yamamoto, K.Owa, M.Shouzakai, R.Matsumoto

    ICSLP'92, Banff   Vol. vol.2   page: pp.1523-1526   1990.10

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  653. The Control of Segmental Duration in Speech Synthesis Using Linguistic Properties Reviewed

    N.Kaiki, K.Takeda, Y.Sagisaka

    ESCA Workshop on Speech Synthesis     page: pp.165-168   1990.9

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  654. A Large-Scale Japanese Speech Database Reviewed

    Y.Sagisaka, M.Abe, K.Takeda, S.Katagiri, T.Umeda, H.Kuwabara

    ICSLP'90 Kobe   Vol. vol.2   page: pp.1089-1092   1990.9

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  655. On the Unit Search Criteria and Algorithms for Speech Synthesis Using Non-uniform Units Reviewed

    K.Takeda, K.Abe, Y.Sagisaka

    ICSLP'90 Kobe   Vol. vol.1   page: pp.341-344   1990.9

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  656. Statistical Analysis for Segmental Duration Rules in Japanese Speech Synthesis Reviewed

    N.Kaiki, K.Takeda, Y.Sagisaka

    ICSLP'90 Kobe   Vol. vol.1   page: pp.17-20   1990.9

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  657. On Unit Selection Algorithms and Their Evaluation in Non-uniform Unit Speech Synthesis Reviewed

    K.Takeda, K.Abe, Y.Sagisaka

    ESCA Workshop on Speech Synthesis     page: pp.35-38   1990.9

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  658. ATR Japanese SpeechDatabase as a Tool of Speech Recognition and Synthesis

    kazuya takeda

    Speech Communication   Vol. 9 ( 4 ) page: 357-363   1990.1

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  659. 選択的に合成単位を用いる規則音声合成(共著) Reviewed

    武田一哉,安部勝雄,匂坂芳典

    電子情報通信学会論文誌   Vol. J73DII ( 12 ) page: 19,451,950   1990.1

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  660. Adaptive Manipulation of Non-uniform Synthesis Units using Multi-level Unit Transcriptions Reviewed

    K.Takeda, K.Abe, Y.Sagisaka, H.Kuwabara

    European Conference on Speech Communication and Technology, Paris   Vol. Vol. 2   page: pp.195-198   1989.9

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  661. On sentence-leuleFactors Governing Segmental Duration inJapanese Reviewed

    K.Takeda, Y.Sagisaka, H.Kuwabara

    Journal of AcousticSociety of America   Vol. 86 ( 6 ) page: 2081-2096   1989.1

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  662. Construction of a Large-scale Japanese Speech Database and Its Management System Reviewed

    H.Kuwabara, K.Takeda, Y.Sagisaka, S.Katagiri, S.Morikawa, T.Watanabe

    ICASSP'89   Vol. vol.1   page: pp.560-563   1989.1

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  663. 研究用日本語音声データベースの構築(共著) Reviewed

    武田一哉 匂酒芳典 片桐滋 桑原尚夫

    日本音響学会誌   Vol. 44 ( 10 ) page: 747-754   1988.1

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  664. Acoustic-Phonetic Labels in a Japanese Speech Database Reviewed

    K.Takeda. Y.Sagisaka, S.Katagiri

    European Conference on Speech Technology, September 1987, Edinburg   Vol. Vol. 2   page: pp.13-16   1987.9

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  665. 部分文仮説の尤度を用いた連続音声認識のための音声区間検出法 Reviewed

    内藤正樹,黒岩眞吾, 山本 誠一, 武田一哉

    電子情報通信学会論文誌   Vol. J80-DII ( 11 ) page: 2895-2903   1987.1

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  666. 住居の音環境に対する都市住民の反応に関する研究 Reviewed

    武田一哉,久野和宏,池谷和夫

    日本音響学会誌   Vol. 42 ( 10 ) page: 768-773   1986.1

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  667. 道路に面する地域について Reviewed

    久野和宏,大原康司,武田一哉

    騒音制御   Vol. 10 ( 1 ) page: 40-43   1986.1

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    Authorship:Lead author   Language:Japanese   Publishing type:Research paper (scientific journal)  

  668. 住環境騒音暴露パターンの解析と住民反応の尺度に関する研究 Reviewed

    武田一哉,久野和宏,池谷和夫

    日本音響学会誌   Vol. 41 ( 12 ) page: 870-876   1985.1

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    Authorship:Lead author   Language:Japanese   Publishing type:Research paper (scientific journal)  

  669. Study on Noise Environment of Residence in Urban Area Reviewed

    K.Kuno, D.Zheng, K.Takeda, K.Ikegaya and Y.Mishina

    Inter Noise 84, Honolulu   Vol. - ( - ) page: -   1984.12

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    Language:English  

  670. 名古屋市域における住居の環境騒音暴露量に関する研究 Reviewed

    久野和宏,今泉勤,奥村陽三,鄭大端,武田一哉、他3名

    日本音響学会誌   Vol. 40 ( 6 ) page: 388-396   1984.1

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    Authorship:Lead author   Language:Japanese   Publishing type:Research paper (scientific journal)  

  671. 都市内住居の騒音暴露量に関する分析 Reviewed

    鄭大端,武田一哉,久野和宏,池谷和夫

    日本音響学会誌   Vol. 40 ( 8 ) page: 546-553   1984.1

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    Authorship:Lead author   Language:Japanese   Publishing type:Research paper (scientific journal)  

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Books 25

  1. Towards Human-Vehicle Harmonization International journal

    Huseyin Abut , Gerhard Schmidt , Kazuya Takeda , Jacob Lambert and John H.L. Hansen( Role: Joint author)

    De Gruyter  2023.3  ( ISBN:9783110994346

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    Total pages:253   Language:English Book type:Scholarly book

    DOI: doi.org/10.1515/9783110981223-toc

  2. Frontiers of Digital Transformation: Applications of the Real-World Data Circulation Paradigm International journal

    Kazuya Takeda, Ichiro Ide, Victor Muhandiki( Role: Edit)

    Springer  2021.6 

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    Language:English

  3. 自動運転

    二宮, 芳樹, 武田, 一哉

    コロナ社  2021.1  ( ISBN:9784339027754

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    Total pages:xi, 273p   Language:Japanese

    CiNii Books

  4. Vehicles, Drivers, and Safety International journal

    John Hansen, Kazuya Takeda, Gerhard Schmidt and Huseyin Abut( Role: Joint author)

    DeGruyter  2020 

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    Language:English Book type:Scholarly book

    DOI: https://doi.org/10.1515/9783110669787

  5. Integrated modeling of driver gaze and vehicle operation behavior during lane changes in

    Chiyomi Miyajima, Masataka Mori, Takatsugu Hirayama, Norihide Kitaoka, and Kazuya Takeda( Role: Joint author)

    De Gruyter  2017.9 

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    Language:English Book type:General book, introductory book for general audience

    De Gruyter,

  6. Vehicle Systems and Driver Modeling

    Abut, Huseyin, Hansen, John, Schmidt, Gerhard, Takeda, Kazuya, Ko, Hanseok( Role: Joint editor)

    De Gruyter  2017.9 

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    Language:Japanese

  7. 行動情報処理 自動運転システムとの共生を目指して 共立スマートセレクション

    武田 一哉, 土井 美和子( Role: Sole author)

    共立出版  2016.1 

  8. Human Harmonized Information Technology, Volume 1 Vertical Impact

    Kazuya TAKEDA( Role: Joint author ,  Chapter 3, Modeling and Detecting Exessive Trust from Behavior Signals: Overview of Research Project and Results)

    Springer  2016 

  9. Content-based driving scene retrieval using driving behavior and environmental driving Signals

    Yiyang Li, Ryo Nakagawa, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda( Role: Joint author)

    Springer Science-Business  2013 

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    Language:English

  10. Digital Signal Processing for In-Vehicle Systems and Safety

    John H.L.Hansen, Pinar Boyraz, Huseyin Abut, Kazuya Takeda( Role: Joint author)

    Springer  2012.2 

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    Language:Japanese

  11. A stochastic approach for modeling lane-change trajectories

    Yoshihiro Nishiwaki, Chiyomi Miyajima, Norihide Kitaoka, and Kazuya Takeda( Role: Joint author)

    Springer, Digital Signal Processing for In-Vehicle Systems and Safety  2012.2 

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    Language:English

  12. Selective listening point audio based on blind signal separation and 3D audio effect

    Takanori Nishino, Motoki Ogasawara, Kenta Niwa, and Kazuya Takeda( Role: Joint author)

    World Scientific  2012.2  ( ISBN:13 978-981-43

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    Language:English

  13. Principles and applications of spatial hearing Analysis of measured head-related transfer functions based on spatio-temporal frequency characteristics

    Yasuko Morimoto, Takanori Nishino, and Kazuya Takeda( Role: Joint author)

    World Scientific  2012.2  ( ISBN:13 978-981-4313

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    Language:English

  14. Use of on-road data in evaluating driver performance metrics

    Lucas Malta, Akira Ozaki, Chiyomi Miyajima, and Kazuya Takeda( Role: Joint author)

    SAE International  2012.1 

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    Language:English

  15. An analysis of the speech under stress using the two-mass vocal fold model

    Xiao Yao, Takatoshi Jitsuhiro, Chiyomi Miyajima, Norihide Kitaoka, Kazuya Takeda( Role: Joint author)

    Proceedings of the Paralinguistic Information and Its Integration in Spoken Dialogue Systems Workshop, Ramon Lopez-Cozar Delgado, Tetsunori Kobayashi eds  2011.9  ( ISBN:978-1-4614-133

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    Language:English

  16. On-line detection of task incompletion for spoken dialog systems using utterance and behavior tag N-gram vectors

    Sunao Hara, Norihide Kitaoka, Kazuya Takeda( Role: Joint author)

    Proceedings of the Paralinguistic Information and Its Integration in Spoken Dialogue Systems Workshop, Ramon Lopez-Cozar Delgado, Tetsunori Kobayashi eds  2011.9  ( ISBN:978-1-4614-13

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    Language:English

  17. Music Recommendation System Based on Human-to-human Conversation Recognition

    Hiromasa Ohashi, Sunao Hara, Norihide Kitaoka, Kazuya Takeda( Role: Joint author)

    Workshop Proceedings of the 7th International Conference on Intelligent Environments: Ambient Intelligence and Smart Environments vol.10,   2011.1  ( ISBN:978-1-60750-7

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    Language:English

  18. Effective Multiple Regression for Robust Single and Multi-channel Speech Recognition

    Weifeng Li, Kazuya Takeda, Fumitada Itakura,( Role: Joint author)

    Bentham Science Publishers, Recent Advances in Robust Speech Recognition Technology, J. Ramirez and J.M. Gorriz eds  2011.1  ( ISBN:eISBN: 978-1-608

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    Language:English

  19. 確率と確率過程

    武田一哉,村瀬洋,中野良平,速水悟,中川聖一,菅谷保之( Role: Joint author)

    オーム社  2010.10 

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    確率と確率過程に関する学部レベルの教科書

  20. Driver Identification Based on Spectral Analsis of Driving Behavioral Signals, Advances for IN-Vehicle and Mobile Systems, Challenges

    Yoshihiro Nishiwaki, Koji Ozawa, Toshihiro Wakita, Chiyomi Miyajima, Katsunobu Itou, and Kazuya Takeda( Role: Joint author)

    Springer  2007.4 

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    Language:English

  21. Advances for In-Vehicle and Mobile Systems -Challenges for International Standards -

    Huseyin Abut, John H.L. Hansen, Kazuya Takeda (Eds)( Role: Joint author)

    Springer publisher  2007.1 

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    Language:English

  22. 音響エレクトロニクス(基礎と応用)

    大賀寿郎,鎌倉友男,斉藤繁実,武田一哉( Role: Joint author)

    培風館  2005.5 

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  23. DSP in Mobile and Vehicular Systems (Eds.)

    Huseyin Abut, John Hansen and Kazuya Takeda (Eds.)( Role: Joint author)

    Springer Publisher  2004.1 

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  24. 音声情報処理

    春日正男,船田哲男,林伸二,武田一哉( Role: Joint author)

    コロナ社  2001.1 

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    音声を用いた情報インタフェース技術に関して、音声符号化、音声信号処理、音声認識合成、音響処理技術、音声システムにかんする最新技術を解説している。

  25. IT-Text 音声認識システム

    鹿野清宏,河原達也,伊藤克亘,武田一哉,山本幹男( Role: Joint author)

    オーム社  2001.1 

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    連続音声認識の基礎技術として、音響分析、音素モデル、言語モデル、デコーダ、に関する最新技術とその利用方法を、添付CDROMに収録された実際のソフトウエアやデータを用いた実習を交えて習得することを目的としている。

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MISC 6

  1. An Evaluation of Speech Waveform Modification Methods towards Improvement of Speech Intelligibility in Noisy Environment

    武山 知弘, 小林 和弘, 戸田 智基, 武田 一哉

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   Vol. 117 ( 368 ) page: 11 - 16   2017.12

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    Language:Japanese   Publisher:電子情報通信学会  

  2. CNNを用いたEnd-to-Endナビゲーションシステムによるつくばチャレンジへの取り組み International coauthorship

    清谷竣也, CARBALLO Alexander, 竹内栄二朗, 宮島千代美, 宮島千代美, 武田一哉, 武田一哉

    計測自動制御学会システムインテグレーション部門講演会(CD-ROM)   Vol. 18th   2017

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    Language:Japanese  

    J-GLOBAL

  3. Investigation of DNN-Based Audio-Visual Speech Recognition (Special Section on Recent Advances in Machine Learning for Spoken Language Processing) Reviewed

    Tamura Satoshi, Ninomiya Hiroshi, Kitaoka Norihide, Osuga Shin, Iribe Yurie, Takeda Kazuya, Hayamizu Satoru

    IEICE Transactions on Information and Systems   Vol. 99 ( 10 ) page: 2444 - 2451   2016.10

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    Language:English   Publisher:The Institute of Electronics, Information and Communication Engineers  

    CiNii Books

  4. Adaptation Methods for Daily Activity Recognition Based on Deep Neural Network

      Vol. 116 ( 189 ) page: 1 - 6   2016.8

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    CiNii Books

  5. Daily Activity Recognition based on Recurrent Neural Networks

      Vol. 116 ( 189 ) page: 7 - 12   2016.8

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    Language:Japanese   Publishing type:Research paper, summary (national, other academic conference)  

    CiNii Books

  6. A-14-20 Comparison of Car-Following Behavior among Different Driver Categories

    Goto Taichi, Miyajima Chiyomi, Li Yiyang, Takeda Kazuya, Hiroike Shinya, Sakamoto Shinobu, Honda Shinichiro, Tsukahara Toshiya, Ito Masayoshi

    Proceedings of the IEICE Engineering Sciences Society/NOLTA Society Conference   Vol. 2016   2016.3

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    Language:Japanese   Publisher:The Institute of Electronics, Information and Communication Engineers  

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Presentations 441

  1. Dance with Rhythmic Frames:コマ送り提示によるVRダンス学習システム

    時田 聡実(名大),石黒 祥生(東大),大谷 健登(名大),西野 隆典(名城大),武田 一哉(名大)

    第27回 一般社団法人情報処理学会シンポジウム インタラクション2023  2023.3.10 

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    Event date: 2023.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  2. UnifiedGeoMap:2D地図と3D地図の組み合わせによる空間情報の把握

    早川 達也,石黒 祥生,大谷 健登,西野 隆典,武田 一哉

    第27回 一般社団法人情報処理学会シンポジウム インタラクション2023  2023.3.8 

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    Event date: 2023.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  3. サッカーにおけるイベント予測に基づく一般化されたチームの守備評価

    梅基 陸平, 中原 啓, 筒井 和詩, 藤井 慶輔

    2022年度スポーツデータサイエンスコンペティション  2023.1.8 

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    Event date: 2023.1

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  4. Efficient Training Method for Point Cloud-based Object Detection Models by Combining Environmental Transitions and Active Learning International conference

    Takumi Yamamoto, Kento Ohtani, Tomoki Hayashi, Alexander Carballo, Kazuya Takeda

    2022.12.9 

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    Event date: 2022.12

    Language:English   Presentation type:Oral presentation (general)  

    Country:Australia