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| Presentation | 2022-06-17 15:00 Blind Source Separation based on Independent Low-Rank Matrix Analysis using Restricted Boltzmann Machines Shotaro Furuta, Takuya Kishida, Toru Nakashika (UEC)  SP2022-8 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this paper, we propose a new blind source separation method that combines independent low-rank source separation (ILRMA), one of the blind source separation methods, and restricted Boltzmann machine (RBM), a generative model. In recent years, many models using blind source separation have been proposed. In particular, ILRMA, which combines independent vector analysis (IVA) and non-negative matrix factorization (NMF), is one of the best methods in terms of separation accuracy and computational cost. A previous study showed that RBM has higher separation accuracy than NMF. Therefore, in order to further improve the separation accuracy, we propose a new blind source separation method that combines RBM and IVA, which can be substituted for NMF, and compares its performance with that of conventional methods. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | blind source separation / independent low-rank matrix analysis / nonnegative matrix factorization / restricted Boltzmann machine / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 81, SP2022-8, pp. 26-29, June 2022. | |
| Paper # | SP2022-8 | |
| Date of Issue | 2022-06-10 (SP) | |
| ISSN | 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) | |
| Download PDF | SP2022-8 |
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| Conference Information | |
| Committee | SP IPSJ-MUS IPSJ-SLP |
| Conference Date | 2022-06-17 - 2022-06-18 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SP |
| Conference Code | 2022-06-SP-MUS-SLP |
| 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 using Restricted Boltzmann Machines |
| Sub Title (in English) | |
| Keyword(1) | blind source separation |
| Keyword(2) | independent low-rank matrix analysis |
| Keyword(3) | nonnegative matrix factorization |
| Keyword(4) | restricted Boltzmann machine |
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| Keyword(8) | |
| 1st Author's Name | Shotaro Furuta |
| 1st Author's Affiliation | The University of Electro-Communications (UEC) |
| 2nd Author's Name | Takuya Kishida |
| 2nd Author's Affiliation | The University of Electro-Communications (UEC) |
| 3rd Author's Name | Toru Nakashika |
| 3rd Author's Affiliation | The University of Electro-Communications (UEC) |
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| Speaker | Author-1 |
| Date Time | 2022-06-17 15:00:00 |
| Presentation Time | 120 minutes |
| Registration for | SP |
| Paper # | SP2022-8 |
| Volume (vol) | vol.122 |
| Number (no) | no.81 |
| Page | pp.26-29 |
| #Pages | 4 |
| Date of Issue | 2022-06-10 (SP) |
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