Presentation 2007/12/13
Noise Suppression Using Multi-noise Model Compositions Integrating Particle Filtering
Takatoshi JITSUHIRO, Tomoji TORIYAMA, Kiyoshi KOGURE,
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Abstract(in English) We propose a noise suppression method based on multi-model compositions using particle filtering. In real environments, input speech for speech recognition includes many kinds of noise signals. For such noisy speech, we have proposed Multi-Model Noise Suppression (MM-NS) that uses many kinds of noise models and their compositions obtained from training data. However, MM-NS only uses static property of noise models, and it is difficult to handle unknown noise distributions. We introduce a particle filter into MM-NS. The distributions of noise models is used as prior distributions of particle filtering. It makes more accurate estimation of noise signals for input data. We evaluated this method using the E-Nightingale task, which contains voice memoranda spoken by nurses during actual work at hospitals. The proposed method obtained higher performance than the original MM-NS.
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Keyword(in English) speech recognition / noise suppression / model composition / particle filter / E-Nightingale project
Paper # NLC2007-66,SP2007-129
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Committee SP
Conference Date 2007/12/13(1days)
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Registration To Speech (SP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Noise Suppression Using Multi-noise Model Compositions Integrating Particle Filtering
Sub Title (in English)
Keyword(1) speech recognition
Keyword(2) noise suppression
Keyword(3) model composition
Keyword(4) particle filter
Keyword(5) E-Nightingale project
1st Author's Name Takatoshi JITSUHIRO
1st Author's Affiliation ATR Knowledge Science Laboratories()
2nd Author's Name Tomoji TORIYAMA
2nd Author's Affiliation ATR Knowledge Science Laboratories
3rd Author's Name Kiyoshi KOGURE
3rd Author's Affiliation ATR Knowledge Science Laboratories
Date 2007/12/13
Paper # NLC2007-66,SP2007-129
Volume (vol) vol.107
Number (no) 406
Page pp.pp.-
#Pages 6
Date of Issue