Presentation 2001/12/13
ATR System for Robust Speech Recognition in Real World Noisy and Channel Environments
Konstantin MARKOV, Tomoko MATSUI, Rainer GRUHN, Jinsong ZHANG, Satoshi NAKAMURA,
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Abstract(in English) This paper presents the ATR speech recognition system designed for the DARPA SPINE2 evaluation task. The system is capable of dealing with speech from highly variable, real world noisy conditions and communication channels. A number of robust techniques were implemented, such as differential spectrum mel-scale cepstrum features, on-line MLLR adaptation and word level hypothesis combination, which led to significant reduction of the word error rate.
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Keyword(in English) noise robustness / online adaptation / hypothesis combination / robust features
Paper # NLC2001-55,SP2001-90
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Committee NLC
Conference Date 2001/12/13(1days)
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Registration To Natural Language Understanding and Models of Communication (NLC)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) ATR System for Robust Speech Recognition in Real World Noisy and Channel Environments
Sub Title (in English)
Keyword(1) noise robustness
Keyword(2) online adaptation
Keyword(3) hypothesis combination
Keyword(4) robust features
1st Author's Name Konstantin MARKOV
1st Author's Affiliation ATR Spoken Language Translation Research Labs.()
2nd Author's Name Tomoko MATSUI
2nd Author's Affiliation ATR Spoken Language Translation Research Labs.
3rd Author's Name Rainer GRUHN
3rd Author's Affiliation ATR Spoken Language Translation Research Labs.
4th Author's Name Jinsong ZHANG
4th Author's Affiliation ATR Spoken Language Translation Research Labs.
5th Author's Name Satoshi NAKAMURA
5th Author's Affiliation ATR Spoken Language Translation Research Labs.
Date 2001/12/13
Paper # NLC2001-55,SP2001-90
Volume (vol) vol.101
Number (no) 520
Page pp.pp.-
#Pages 7
Date of Issue