Presentation 2015-03-02
Optimization of impulse responses for model training in reverberant speech recognition
Takahiro FUKUMORI, Masato NAKAYAMA, Takanobu NISHIURA, Yoichi YAMASHITA,
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Abstract(in English) The reverberant speech degrades the speech recognition performance in the field of distant-talking speech. As one of approaches against the reverberation, a method has been studied by constructing an acoustic model trained with the reverberant speech. There is, however, a problem that the reverberation time, which is an unique value in a room, has a limitation for an improvement of speech recognition performance because speech recognition performance greatly depends on the arrangement of a speaker and a microphone. To overcome this problem, we have already proposed a construction method of an optimum acoustic model based on D value. In this method, an acoustic model is constructed by using many impulse responses measured under the conditions with different D value. The proposed method could improve speech recognition performance in comparison with a conventional method. In this paper, we try to optimize impulse responses for training an acoustic model in terms of a border time of D value and a number of impulse responses. In evaluation experiments, we confirmed higher speech recognition performance by using nine impulse responses with different reverberation time and D_<50>.
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Keyword(in English) Speech recognition / Reverberation / Acoustic model / Acoustic parameters
Paper # EA2014-78,SIP2014-119,SP2014-141
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Committee EA
Conference Date 2015/2/23(1days)
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Registration To Engineering Acoustics (EA)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Optimization of impulse responses for model training in reverberant speech recognition
Sub Title (in English)
Keyword(1) Speech recognition
Keyword(2) Reverberation
Keyword(3) Acoustic model
Keyword(4) Acoustic parameters
1st Author's Name Takahiro FUKUMORI
1st Author's Affiliation Graduate School of Information Science and Engineering, Ritsumeikan University()
2nd Author's Name Masato NAKAYAMA
2nd Author's Affiliation College of Information Science and Engineering, Ritsumeikan University
3rd Author's Name Takanobu NISHIURA
3rd Author's Affiliation College of Information Science and Engineering, Ritsumeikan University
4th Author's Name Yoichi YAMASHITA
4th Author's Affiliation College of Information Science and Engineering, Ritsumeikan University
Date 2015-03-02
Paper # EA2014-78,SIP2014-119,SP2014-141
Volume (vol) vol.114
Number (no) 473
Page pp.pp.-
#Pages 6
Date of Issue