Paper Abstract and Keywords |
Presentation |
2012-06-08 15:10
Performance comparison of MMSE and sparse models in source separation using multichannel Wiener filter Ryutaro Sakanashi, Shigeki Miyabe, Takeshi Yamada, Shoji Makino (Univ. Tsukuba) EA2012-43 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Multichannel Wiener filter proposed by Duong {\it et al}. can conduct underdetermined blind source separation (BSS) with low distortion. This method assumes that the observed signal is the superimposition of the multichannel source images generated from multivariate normal distributions. The covariance matrix in each time-frequency slot is estimated by EM algorithm which treats the source images as the latent variables. Using the estimated parameters, the source images are separated as the maximum a posteriori estimate. It is worth nothing that this method does not use assumption of sparseness, which is usually used in underdetermined BSS. In this paper we investigate the effectiveness of the three features of Duong's method, i.e., the source image model with multivariate normal distribution, the observation model without sparseness assumption, and the multichannel Wiener filter. We newly formulate the BSS method with the similar source image model and the different observation model assuming sparseness, and compare with the Duong's method and the conventional binary masking. Experimental results confirmed the effectiveness of all the three features of Duong's method. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Underdetermined blind source separation / sparseness / time-frequency masking / multivariate normal distribution / EM algorithm / multichannel Wiener filter / / |
Reference Info. |
IEICE Tech. Rep., vol. 112, no. 76, EA2012-43, pp. 61-66, June 2012. |
Paper # |
EA2012-43 |
Date of Issue |
2012-06-01 (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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EA2012-43 |
Conference Information |
Committee |
EA |
Conference Date |
2012-06-08 - 2012-06-08 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Yamaha Co. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
General topics |
Paper Information |
Registration To |
EA |
Conference Code |
2012-06-EA |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Performance comparison of MMSE and sparse models in source separation using multichannel Wiener filter |
Sub Title (in English) |
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Keyword(1) |
Underdetermined blind source separation |
Keyword(2) |
sparseness |
Keyword(3) |
time-frequency masking |
Keyword(4) |
multivariate normal distribution |
Keyword(5) |
EM algorithm |
Keyword(6) |
multichannel Wiener filter |
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1st Author's Name |
Ryutaro Sakanashi |
1st Author's Affiliation |
University of Tsukuba (Univ. Tsukuba) |
2nd Author's Name |
Shigeki Miyabe |
2nd Author's Affiliation |
University of Tsukuba (Univ. Tsukuba) |
3rd Author's Name |
Takeshi Yamada |
3rd Author's Affiliation |
University of Tsukuba (Univ. Tsukuba) |
4th Author's Name |
Shoji Makino |
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University of Tsukuba (Univ. Tsukuba) |
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Speaker |
Author-1 |
Date Time |
2012-06-08 15:10:00 |
Presentation Time |
25 minutes |
Registration for |
EA |
Paper # |
EA2012-43 |
Volume (vol) |
vol.112 |
Number (no) |
no.76 |
Page |
pp.61-66 |
#Pages |
6 |
Date of Issue |
2012-06-01 (EA) |
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