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| Paper Abstract and Keywords | ||
| Presentation | 2022-12-23 11:10 Enhancement of Audio Signals Using Learning from Positive and Unlabelled Data Nobutaka Ito, Masashi Sugiyama (UTokyo)  IBISML2022-56 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Audio signal enhancement (SE) is the task of extracting a desired class of sounds (a “signal”) from an observed sound mixture (a “noisy signal”). Although the mainstream SE approach is supervised learning, it is physically impossible to record required parallel training data consisting of both noisy signals and the corresponding clean (i.e., noise-free) signals. These data are thus synthesised in practice, which can severely degrade real-world performance. Here we propose an SE method using learning from positive and unlabelled data. It enables SE using non-parallel training data consisting of noisy signals and noise, which can be recorded easily. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | audio signal enhancement / learning from positive and unlabelled data / weakly supervised learning / non-parallel data / convolutional neural networks / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 325, IBISML2022-56, pp. 94-100, Dec. 2022. | |
| Paper # | IBISML2022-56 | |
| Date of Issue | 2022-12-15 (IBISML) | |
| 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 | IBISML2022-56 |
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| Conference Information | |
| Committee | IBISML |
| Conference Date | 2022-12-22 - 2022-12-23 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kyoto University |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Machine Learning, etc. |
| Paper Information | |
| Registration To | IBISML |
| Conference Code | 2022-12-IBISML |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Enhancement of Audio Signals Using Learning from Positive and Unlabelled Data |
| Sub Title (in English) | |
| Keyword(1) | audio signal enhancement |
| Keyword(2) | learning from positive and unlabelled data |
| Keyword(3) | weakly supervised learning |
| Keyword(4) | non-parallel data |
| Keyword(5) | convolutional neural networks |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Nobutaka Ito |
| 1st Author's Affiliation | the University of Tokyo (UTokyo) |
| 2nd Author's Name | Masashi Sugiyama |
| 2nd Author's Affiliation | the University of Tokyo (UTokyo) |
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| Speaker | Author-1 |
| Date Time | 2022-12-23 11:10:00 |
| Presentation Time | 20 minutes |
| Registration for | IBISML |
| Paper # | IBISML2022-56 |
| Volume (vol) | vol.122 |
| Number (no) | no.325 |
| Page | pp.94-100 |
| #Pages | 7 |
| Date of Issue | 2022-12-15 (IBISML) |
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