Paper Abstract and Keywords |
Presentation |
2019-10-28 14:00
FastMNMF based on multivariant complex Student's t distribution for blind source separation Keigo Kamo, Yuki Kubo, Norihiro Takamune (UTokyo), Daichi Kitamura (Kagawa NCIT), Hiroshi Saruwatari (UTokyo), Yu Takahashi, Kazunobu Kondo (Yamaha) EA2019-40 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
FastMNMF is a blind source separation technique, which is an accelerated algorithm of multichannel nonnegative matrix factorization under the assumption of jointly diagonalizable spatial covariance matrices. Source signals' spectrograms were assumed to follow a multivariate complex Gaussian distribution in FastMNMF. In this paper, we propose the model extension of FastMNMF to a multivariate complex Student's textit{t} distribution. We derive a new parameter update rule using the auxiliary-function-based method, and show that the proposed method outperforms the conventional Gaussian-model-based FastMNMF. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
blind source separation / spatial covariance model / multivariate complex Student's t distriburion / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 253, EA2019-40, pp. 23-29, Oct. 2019. |
Paper # |
EA2019-40 |
Date of Issue |
2019-10-21 (EA) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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) |
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EA2019-40 |
Conference Information |
Committee |
EA ASJ-H |
Conference Date |
2019-10-28 - 2019-10-29 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
NHK Science&Technology Research Lab. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Engineering/Electro Acoustics, Psychological and Physiological Acoustics, High-Reality Audio, Spatial Audio, and Related Topics |
Paper Information |
Registration To |
EA |
Conference Code |
2019-10-EA-H |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
FastMNMF based on multivariant complex Student's t distribution for blind source separation |
Sub Title (in English) |
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Keyword(1) |
blind source separation |
Keyword(2) |
spatial covariance model |
Keyword(3) |
multivariate complex Student's t distriburion |
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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 (Kagawa NCIT) |
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 |
2019-10-28 14:00:00 |
Presentation Time |
25 minutes |
Registration for |
EA |
Paper # |
EA2019-40 |
Volume (vol) |
vol.119 |
Number (no) |
no.253 |
Page |
pp.23-29 |
#Pages |
7 |
Date of Issue |
2019-10-21 (EA) |
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