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| Presentation | 2016-08-25 13:35 Diversity-driven Semi-supervised Ensemble DNN Acoustic Model Training Sheng Li (Kyoto Univ.), Xugang Lu (NICT), Shinsuke Sakai, Tatsuya Kawahara (Kyoto Univ.)  SP2016-40 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | We focus on effective training DNN (Deep Neural Network) acoustic models for Chinese spoken lectures with only limited labeled speech and abundant unlabeled speech. Unlike selectively using the unlabeled data in most semi-supervised DNN training methods and working only under supervised setting in previous ensemble DNN training methods, we work on more generalized ensemble training method for both labeled and unlabeled data. In our proposed method, a pair of models is trained in parallel with diverse labels generated for unlabeled data. Together with the standard cross entropy, the KL divergence between each individual model over unlabeled data is incorporated during training. Experiments show that our proposed method can effectively utilize unlabeled data and outperforms other well-established semi-supervised methods. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Speech recognition / Acoustic model / DNN / Semi-superivsed training / Ensemble training / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 116, no. 189, SP2016-40, pp. 71-76, Aug. 2016. | |
| Paper # | SP2016-40 | |
| Date of Issue | 2016-08-17 (SP) | |
| 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) | |
| Download PDF | SP2016-40 |
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| Conference Information | |
| Committee | SP |
| Conference Date | 2016-08-24 - 2016-08-25 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | ACCMS, Kyoto Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Audio event processing, etc. |
| Paper Information | |
| Registration To | SP |
| Conference Code | 2016-08-SP |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Diversity-driven Semi-supervised Ensemble DNN Acoustic Model Training |
| Sub Title (in English) | |
| Keyword(1) | Speech recognition |
| Keyword(2) | Acoustic model |
| Keyword(3) | DNN |
| Keyword(4) | Semi-superivsed training |
| Keyword(5) | Ensemble training |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Sheng Li |
| 1st Author's Affiliation | Kyoto University (Kyoto Univ.) |
| 2nd Author's Name | Xugang Lu |
| 2nd Author's Affiliation | National Institute of Information and Communications Technology (NICT) |
| 3rd Author's Name | Shinsuke Sakai |
| 3rd Author's Affiliation | Kyoto University (Kyoto Univ.) |
| 4th Author's Name | Tatsuya Kawahara |
| 4th Author's Affiliation | Kyoto University (Kyoto Univ.) |
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| Speaker | Author-1 |
| Date Time | 2016-08-25 13:35:00 |
| Presentation Time | 25 minutes |
| Registration for | SP |
| Paper # | SP2016-40 |
| Volume (vol) | vol.116 |
| Number (no) | no.189 |
| Page | pp.71-76 |
| #Pages | 6 |
| Date of Issue | 2016-08-17 (SP) |
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