Presentation 2005/12/14
Sequential Non-Stationary Noise Tarcking Based on Switching Dynamical System and Particle Filtering
Masakiyo FUJIMOTO, Satoshi NAKAMURA,
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Abstract(in English) This paper addresses a speech recognition problem in non-stationary noise environments : the estimation of noise sequences. To solve this problem, we present a particle filter-based sequential noise estimation method for the front-end processing of speech recognition. In the proposed method, the particle filter is defined by a dynamical system based on Polyak averaging and feedback. We also introduce a switching dynamical system into the particle filter to cope with non-stationarity of the environment noise. In the evaluation results, we observed that the proposed method improves speech recognition accuracy in the results of non-stationary noise environments by a noise compensation method with stationary noise assumptions.
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Keyword(in English) noisy speech recognition / non-stationary noise / particle filter / switching dynamical system
Paper # NLC2005-58,SP2005-91
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Committee NLC
Conference Date 2005/12/14(1days)
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Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Sequential Non-Stationary Noise Tarcking Based on Switching Dynamical System and Particle Filtering
Sub Title (in English)
Keyword(1) noisy speech recognition
Keyword(2) non-stationary noise
Keyword(3) particle filter
Keyword(4) switching dynamical system
1st Author's Name Masakiyo FUJIMOTO
1st Author's Affiliation ATR Spoken Language Communication Research Laboratories()
2nd Author's Name Satoshi NAKAMURA
2nd Author's Affiliation ATR Spoken Language Communication Research Laboratories
Date 2005/12/14
Paper # NLC2005-58,SP2005-91
Volume (vol) vol.105
Number (no) 493
Page pp.pp.-
#Pages 6
Date of Issue