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Paper Abstract and Keywords
Presentation 2018-02-16 13:10
The effect of increasing the number of channels with multi-channel non-negative matrix factorization for noisy speech recognition
Takanobu Uramoto (Oita Univ.), Youhei Okato, Toshiyuki Hanazawa (Mitsubishi Electric), Iori Miura, Shingo Uenohara, Ken'ich Furuya (Oita Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) Nonnegative Matrix Factorization (NMF) factorizes a non-negative matrix into two non-negative matrices. In the field of acoustics, Multichannel NMF (MNMF) has been proposed. MNMF utilizes spatial information by multichannel expansion of NMF and can perform high-accurate sound source separation. However, the conventional MNMF tends to be trapped by local minima because their models have too many free parameters and this causes initial value dependencies of the separation performance. In addition, as the number of channels increases, this initial value dependency becomes more significant. This paper focuses on spatial correlation matrices that have the most significant initial-value dependencies. We propose initial-value methods of spatial correlation matrices from binary-mask based separated data and from the steering vector obtained by mask emphasis based on EM algorithm. Automatic speech recognition experiments of the signals observed at 2ch and 6ch under noisy showed a decrease in word error rate for both channels over random initialization.Since high recognition performance was obtained with 6 ch, we confirmed the effectiveness of initialization by the proposed method and the effect of improving recognition performance by increasing the number of channels.
Keyword (in Japanese) (See Japanese page) 
(in English) sound source separation / noise reduction / nonnegative matrix factorization (NMF) / multi-channel NMF / automatic speech recognition / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 430, EA2017-99, pp. 33-38, Feb. 2018.
Paper # EA2017-99 
Date of Issue 2018-02-08 (EA) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380

Conference Information
Committee EA  
Conference Date 2018-02-15 - 2018-02-16 
Place (in Japanese) (See Japanese page) 
Place (in English) Pref. Univ. Hiroshima 
Topics (in Japanese) (See Japanese page) 
Topics (in English) General topics 
Paper Information
Registration To EA 
Conference Code 2018-02-EA 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) The effect of increasing the number of channels with multi-channel non-negative matrix factorization for noisy speech recognition 
Sub Title (in English)  
Keyword(1) sound source separation  
Keyword(2) noise reduction  
Keyword(3) nonnegative matrix factorization (NMF)  
Keyword(4) multi-channel NMF  
Keyword(5) automatic speech recognition  
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1st Author's Name Takanobu Uramoto  
1st Author's Affiliation Oita University (Oita Univ.)
2nd Author's Name Youhei Okato  
2nd Author's Affiliation Mitsubishi Electric Corporation Information technology R&D center (Mitsubishi Electric)
3rd Author's Name Toshiyuki Hanazawa  
3rd Author's Affiliation Mitsubishi Electric Corporation Information technology R&D center (Mitsubishi Electric)
4th Author's Name Iori Miura  
4th Author's Affiliation Oita University (Oita Univ.)
5th Author's Name Shingo Uenohara  
5th Author's Affiliation Oita University (Oita Univ.)
6th Author's Name Ken'ich Furuya  
6th Author's Affiliation Oita University (Oita Univ.)
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Speaker
Date Time 2018-02-16 13:10:00 
Presentation Time 30 
Registration for EA 
Paper # IEICE-EA2017-99 
Volume (vol) IEICE-117 
Number (no) no.430 
Page pp.33-38 
#Pages IEICE-6 
Date of Issue IEICE-EA-2018-02-08 


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