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| Presentation | 2014-12-16 13:30 [Poster Presentation] speech selection and environmental adaptation for asynchronous speech recording based on deep neural network Bo Ren, Longbiao Wang (Nagaoka Univ. of Tech.), Atsuhiko Kai (Shizuoka Univ.)  SP2014-121 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this paper, we propose a robust distant-talking speech recognition system with asynchronous speech recording. This is implemented by combining automatic asynchronous speech (microphone or mobile terminal) selection and environmental adaptation with deep neural network. Although applications using mobile terminals have attracted increasing attention, there are few studies that focus on distant-talking speech recognition with asynchronous mobile terminals. For the system proposed in this paper, by using bottleneck features (BNFs) from a deep neural network (DNN) rather than the conventional mel-frequency cesptral coefficients (MFCCs), we adopted the state-of-the-art deep neural network acoustic model, environmental adaptation and automatic asynchronous speech selection. The proposed method was evaluated by using a reverberant WSJCAM0 corpus, which was emitted by a loudspeaker and recorded in a meeting room with multiple speakers by far-field multiple mobile terminals. By invoking the bottleneck features and DNN acoustic model with automatic asynchronous speech selection and environmental adaptation, the average Word Error Rate (WER) was reduced from 55.32% of the baseline system to 19.38%, i.e. the relative error reduction rate was 64.97%. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | distant-talking speech recognition / tandem DNN / hybrid DNN / model adaptation / asynchronous speech / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 114, no. 365, SP2014-121, pp. 129-134, Dec. 2014. | |
| Paper # | SP2014-121 | |
| Date of Issue | 2014-12-08 (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 | SP2014-121 |
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| Conference Information | |
| Committee | NLC IPSJ-NL SP IPSJ-SLP JSAI-SLUD |
| Conference Date | 2014-12-15 - 2014-12-17 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Tokyo Institute of Technology (Suzukakedai Campus) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | The 6th Symposium on Collective Knowlege |
| Paper Information | |
| Registration To | SP |
| Conference Code | 2014-12-NLC-NL-SP-SLP-SLUD |
| Language | English (Japanese title is available) |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | speech selection and environmental adaptation for asynchronous speech recording based on deep neural network |
| Sub Title (in English) | |
| Keyword(1) | distant-talking speech recognition |
| Keyword(2) | tandem DNN |
| Keyword(3) | hybrid DNN |
| Keyword(4) | model adaptation |
| Keyword(5) | asynchronous speech |
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| 1st Author's Name | Bo Ren |
| 1st Author's Affiliation | Nagaoka University of Technology (Nagaoka Univ. of Tech.) |
| 2nd Author's Name | Longbiao Wang |
| 2nd Author's Affiliation | Nagaoka University of Technology (Nagaoka Univ. of Tech.) |
| 3rd Author's Name | Atsuhiko Kai |
| 3rd Author's Affiliation | Shizuoka University (Shizuoka Univ.) |
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| Speaker | Author-1 |
| Date Time | 2014-12-16 13:30:00 |
| Presentation Time | 90 minutes |
| Registration for | SP |
| Paper # | SP2014-121 |
| Volume (vol) | vol.114 |
| Number (no) | no.365 |
| Page | pp.129-134 |
| #Pages | 6 |
| Date of Issue | 2014-12-08 (SP) |
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