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Paper Abstract and Keywords
Presentation 2020-03-02 10:10
Multichannel NMF with Joint-Diagonalizable Constraint Based on Generalized Gaussian Distribution for Blind Source Separation
Keigo Kamo, Yuki Kubo, Norihiro Takamune (UTokyo), Daichi Kitamura (NIT Kagawa), Hiroshi Saruwatari (UTokyo), Yu Takahashi, Kazunobu Kondo (Yamaha) EA2019-103 SIP2019-105 SP2019-52
Abstract (in Japanese) (See Japanese page) 
(in English) Multichannel nonnegative matrix factorization (MNMF) is a blind source separation technique, which employs the full-rank spatial covariance matrices and can simulate the situations where the reverberation is strong and the sources are not point sources. Source signals' spectrograms were assumed to follow a multivariate complex Gaussian distribution in MNMF. In this paper, we propose the model extension of MNMF to a multivariate complex generalized Gaussian distribution and derive a new parameter update rule using the auxiliary-function-based method, especially in the sub-Gaussian model. Since the cost function of MNMF of this multivariate complex generalized Gaussian model is hard to minimize, we additionally introduce the joint-diagonalizable constraint, which is the same one of FastMNMF, to MNMF, and transform the cost function to the form to which we can apply the auxiliary functions, deriving the valid parameter update rules. From blind source separation experiments, we show that the proposed method outperforms the conventional methods in source-separation accuracy.
Keyword (in Japanese) (See Japanese page) 
(in English) blind source separation / spatial covariance model / joint diagonalization / multivariate complex sub-Gaussian distribution / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 439, EA2019-103, pp. 13-19, March 2020.
Paper # EA2019-103 
Date of Issue 2020-02-24 (EA, SIP, SP) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF EA2019-103 SIP2019-105 SP2019-52

Conference Information
Committee SP EA SIP  
Conference Date 2020-03-02 - 2020-03-03 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Industry Support Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To EA 
Conference Code 2020-03-SP-EA-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Multichannel NMF with Joint-Diagonalizable Constraint Based on Generalized Gaussian Distribution for Blind Source Separation 
Sub Title (in English)  
Keyword(1) blind source separation  
Keyword(2) spatial covariance model  
Keyword(3) joint diagonalization  
Keyword(4) multivariate complex sub-Gaussian distribution  
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1st Author's Name Keigo Kamo  
1st Author's Affiliation The University of Tokyo (UTokyo)
2nd Author's Name Yuki Kubo  
2nd Author's Affiliation The University of Tokyo (UTokyo)
3rd Author's Name Norihiro Takamune  
3rd Author's Affiliation The University of Tokyo (UTokyo)
4th Author's Name Daichi Kitamura  
4th Author's Affiliation National Institute of Technology, Kagawa Collage (NIT Kagawa)
5th Author's Name Hiroshi Saruwatari  
5th Author's Affiliation The University of Tokyo (UTokyo)
6th Author's Name Yu Takahashi  
6th Author's Affiliation Yamaha Corporation (Yamaha)
7th Author's Name Kazunobu Kondo  
7th Author's Affiliation Yamaha Corporation (Yamaha)
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Speaker Author-1 
Date Time 2020-03-02 10:10:00 
Presentation Time 25 minutes 
Registration for EA 
Paper # EA2019-103, SIP2019-105, SP2019-52 
Volume (vol) vol.119 
Number (no) no.439(EA), no.440(SIP), no.441(SP) 
Page pp.13-19 
#Pages
Date of Issue 2020-02-24 (EA, SIP, SP) 


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