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| Presentation | 2019-03-15 10:25 Neural Language Models based on Conditional Hierarchical Recurrent Encoder-Decoder for Multi-Party Conversational Speech Recognition Ryo Masumura, Tomohiro Tanaka, Atsushi Ando, Takanobu Oba, Yushi Aono (NTT)  EA2018-131 SIP2018-137 SP2018-93 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | This paper presents fully neural network based language models (LMs) that can leverage long-range conversational contexts beyond utterance boundaries for enhancing automatic speech recognition performance of role play dialogues such as contact center dialogues or service center dialogues. The proposed methods called role play dialogue aware LMs are composed by extending hierarchical recurrent encoder-decoder modeling so as to handle speaker role information in the role play dialogues. This enables us to leverage sequential conversational contexts from start-of-conversation to a current word in a current utterance for estimating the generative probability of a next word. Experiments using contact center dialogue data sets demonstrate the effectiveness of the proposed method in terms of perplexity and word error rate. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | multi-party conversational automatic speech recognition / role play dialogue aware language models / conditional hierarchical recurrent encoder-decoder / contact center dialogues / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 118, no. 497, SP2018-93, pp. 191-196, March 2019. | |
| Paper # | SP2018-93 | |
| Date of Issue | 2019-03-07 (EA, SIP, 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 | EA2018-131 SIP2018-137 SP2018-93 |
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| Conference Information | |
| Committee | EA SIP SP |
| Conference Date | 2019-03-14 - 2019-03-15 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | i+Land nagasaki (Nagasaki-shi) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Engineering/Electro Acoustics, Signal Processing, Speech, and Related Topics |
| Paper Information | |
| Registration To | SP |
| Conference Code | 2019-03-EA-SIP-SP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Neural Language Models based on Conditional Hierarchical Recurrent Encoder-Decoder for Multi-Party Conversational Speech Recognition |
| Sub Title (in English) | |
| Keyword(1) | multi-party conversational automatic speech recognition |
| Keyword(2) | role play dialogue aware language models |
| Keyword(3) | conditional hierarchical recurrent encoder-decoder |
| Keyword(4) | contact center dialogues |
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| 1st Author's Name | Ryo Masumura |
| 1st Author's Affiliation | NTT Corporation (NTT) |
| 2nd Author's Name | Tomohiro Tanaka |
| 2nd Author's Affiliation | NTT Corporation (NTT) |
| 3rd Author's Name | Atsushi Ando |
| 3rd Author's Affiliation | NTT Corporation (NTT) |
| 4th Author's Name | Takanobu Oba |
| 4th Author's Affiliation | NTT Corporation (NTT) |
| 5th Author's Name | Yushi Aono |
| 5th Author's Affiliation | NTT Corporation (NTT) |
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| Speaker | Author-1 |
| Date Time | 2019-03-15 10:25:00 |
| Presentation Time | 25 minutes |
| Registration for | SP |
| Paper # | EA2018-131, SIP2018-137, SP2018-93 |
| Volume (vol) | vol.118 |
| Number (no) | no.495(EA), no.496(SIP), no.497(SP) |
| Page | pp.191-196 |
| #Pages | 6 |
| Date of Issue | 2019-03-07 (EA, SIP, SP) |
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