Paper Abstract and Keywords |
Presentation |
2017-10-22 09:00
[Invited Talk]
Blind source separation based on independent low-rank matrix analysis Daichi Kitamura (UT), Nobutaka Ono (NII), Hiroshi Sawada, Hirokazu Kameoka (NTT), Hiroshi Saruwatari (UT) EA2017-56 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In this paper, we propose a new effective algorithm for blind source separation problem (BSS) called independent low-rank matrix analysis (ILRMA). ILRMA is a unified method of independent vector analysis (IVA) and nonnegative matrix factorization (NMF) and can be interpreted as a natural extension of the source separation theory based on statistical independence. Also, ILRMA is identical to a special case of multichannel NMF (MNMF), and this fact reveals the relationship between the state-of-the-art BSS techniques including IVA and MNMF. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
blind source separation / independent component analysis / nonnegative matrix factorization / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 255, EA2017-56, pp. 73-80, Oct. 2017. |
Paper # |
EA2017-56 |
Date of Issue |
2017-10-14 (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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EA2017-56 |
Conference Information |
Committee |
EA ASJ-H |
Conference Date |
2017-10-21 - 2017-10-22 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Ushidake-Onsen |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Beginners Session(Engineering/Electro Acoustics, Psychological and Physiological Acoustics, and Related Topics) |
Paper Information |
Registration To |
EA |
Conference Code |
2017-10-EA-H |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Blind source separation based on independent low-rank matrix analysis |
Sub Title (in English) |
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Keyword(1) |
blind source separation |
Keyword(2) |
independent component analysis |
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nonnegative matrix factorization |
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1st Author's Name |
Daichi Kitamura |
1st Author's Affiliation |
The University of Tokyo (UT) |
2nd Author's Name |
Nobutaka Ono |
2nd Author's Affiliation |
National Institute of Informatics (NII) |
3rd Author's Name |
Hiroshi Sawada |
3rd Author's Affiliation |
Nippon Telegraph and Telephone Corporation (NTT) |
4th Author's Name |
Hirokazu Kameoka |
4th Author's Affiliation |
Nippon Telegraph and Telephone Corporation (NTT) |
5th Author's Name |
Hiroshi Saruwatari |
5th Author's Affiliation |
The University of Tokyo (UT) |
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Speaker |
Author-1 |
Date Time |
2017-10-22 09:00:00 |
Presentation Time |
60 minutes |
Registration for |
EA |
Paper # |
EA2017-56 |
Volume (vol) |
vol.117 |
Number (no) |
no.255 |
Page |
pp.73-80 |
#Pages |
8 |
Date of Issue |
2017-10-14 (EA) |
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