Driver's irritation detection using speech recognition results (音声言語情報処理)
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概要
- 論文の詳細を見る
In this work we present our efforts towards the multi-modal estimation of a driver's affective state under naturalistic conditions. Multi-modal data from 18 subjects (2.3h) who interacted with an automatic speech recognition system while driving are recorded. A transcription protocol is designed to provide a meaningful description of the driving environment. A data fusion model based on Bayesian network is proposed and used for estimating a driver's level of irritation. Information on transcription labels, physiological signals, driving behavior and speech recognition are integrated. Preliminary results are very encouraging.
- 一般社団法人情報処理学会の論文
- 2008-12-02
著者
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TAKEDA Kazuya
Nagoya University
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Takeda Kazuya
Nagoya Univ.
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Takeda K
Nagoya Univ. Nagoya Jpn
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Takeda Kazuya
Graduate School Of Information Science Nagoya University
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Takeda Kazuya
Nagoya Univ. Nagoya‐shi Jpn
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MIYAJIMA Chiyomi
Nagoya University
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Malta Lucas
Graduate School Of Information Science Nagoya University
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Ozaki Akira
Graduate School Of Information Science Nagoya University
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Miyajima Chiyomi
The Graduate School Of Information Science Nagoya University
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Miyajima Chiyomi
Graduate School of Information Science, Nagoya University
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Kitaoka Norihide
Graduate School of Information Science, Nagoya University
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Takeda Kazuya
Graduate School Of Information Science At Nagoya University
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Kitaoka Norihide
Nagoya Univ.
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Takeda Kazuya
Graduate School of Engineering, Nagoya University:Center for Integrated Acoustic Information Research, Nagoya University
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TAKEDA Kazuya
Graduate School of Engineering, Nagoya University
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