Faculty Profiles - TAKEDA, Kazuya

Papers - TAKEDA, Kazuya

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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

Language：English Publishing type：Part of collection (book)

© 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

Scopus

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

Publishing type：Research paper (international conference proceedings) Publisher：ISCA-INT SPEECH COMMUNICATION ASSOC

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

Web of Science

Scopus

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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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Papers - TAKEDA, Kazuya