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| Presentation | 2022-03-01 14:45 Target speaker extraction based on conditional variational autoencoder and directional information in underdetermined condition Rui Wang, Li Li, Tomoki Toda (Nagoya Univ)  EA2021-76 SIP2021-103 SP2021-61 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | This paper deals with a dual-channel target speaker extraction problem in underdetermined conditions. A blind source separation framework based on the demixing matrix estimation with deep source models has achieved reasonably high separation performance in determined conditions, but its performance is still limited in underdetermined conditions. For the dual-channel target speaker extraction, it is expected that the additional directional information is a useful cue, and the choice of the source model is crucial to the performance. In this report, we propose a target speaker extraction method by combining geometrical constraint-based target selection capability, more powerful source modeling, and nonlinear postprocessing. In the demixing matrix estimation, the target directional information is used as a soft constraint, and two conditional variational autoencoders are used to model a single speaker's speech and interference mixture speech, respectively. As the postprocessing, a time-frequency mask estimated from the separated interference mixture speech is used to extract the target speaker's speech. Experimental results have demonstrated that the proposed method outperforms baseline methods. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Underdetermined target speaker extraction / geometrical constraints / variational autoencoder (VAE) / interference mixture speech modeling / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 383, EA2021-76, pp. 76-81, March 2022. | |
| Paper # | EA2021-76 | |
| Date of Issue | 2022-02-22 (EA, SIP, 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 | EA2021-76 SIP2021-103 SP2021-61 |
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| Conference Information | |
| Committee | EA SIP SP IPSJ-SLP |
| Conference Date | 2022-03-01 - 2022-03-02 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | EA |
| Conference Code | 2022-03-EA-SIP-SP-SLP |
| Language | English (Japanese title is available) |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Target speaker extraction based on conditional variational autoencoder and directional information in underdetermined condition |
| Sub Title (in English) | |
| Keyword(1) | Underdetermined target speaker extraction |
| Keyword(2) | geometrical constraints |
| Keyword(3) | variational autoencoder (VAE) |
| Keyword(4) | interference mixture speech modeling |
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| 1st Author's Name | Rui Wang |
| 1st Author's Affiliation | Nagoya University (Nagoya Univ) |
| 2nd Author's Name | Li Li |
| 2nd Author's Affiliation | Nagoya University (Nagoya Univ) |
| 3rd Author's Name | Tomoki Toda |
| 3rd Author's Affiliation | Nagoya University (Nagoya Univ) |
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| Speaker | Author-1 |
| Date Time | 2022-03-01 14:45:00 |
| Presentation Time | 25 minutes |
| Registration for | EA |
| Paper # | EA2021-76, SIP2021-103, SP2021-61 |
| Volume (vol) | vol.121 |
| Number (no) | no.383(EA), no.384(SIP), no.385(SP) |
| Page | pp.76-81 |
| #Pages | 6 |
| Date of Issue | 2022-02-22 (EA, SIP, SP) |
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