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Paper Abstract and Keywords
Presentation 2020-09-10 15:25
Unsupervised Domain Adaptation for Dialogue Sequence Labeling -- Application to Contact Center Tasks --
Shota Orihashi, Naoki Makishima, Mana Ihori, Akihiko Takashima, Tomohiro Tanaka, Ryo Masumura (NTT) NLC2020-8
Abstract (in Japanese) (See Japanese page) 
(in English) This paper presents an unsupervised domain adaptation for utterance-level sequence labeling of conversation in a contact center. For the sequence labeling, a method utilizing two networks that understand short-term context for each utterance and long-term context between utterances is effective. However, a large amount of labeled training data is required to train the networks. In this paper, we apply unsupervised domain adaptation that trains target domain model using labeled source domain data and unlabeled target domain data. In order to efficiently remove the domain dependency, we perform adversarial training utilizing domain discriminators for each context-understanding network.
Keyword (in Japanese) (See Japanese page) 
(in English) dialogue sequence labeling / unsupervised domain adaptation / adversarial training / / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 166, NLC2020-8, pp. 34-39, Sept. 2020.
Paper # NLC2020-8 
Date of Issue 2020-09-03 (NLC) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Copyright
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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 NLC2020-8

Conference Information
Committee NLC  
Conference Date 2020-09-10 - 2020-09-10 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) The Sixteenth Text Analytics Symposium 
Paper Information
Registration To NLC 
Conference Code 2020-09-NLC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Unsupervised Domain Adaptation for Dialogue Sequence Labeling 
Sub Title (in English) Application to Contact Center Tasks 
Keyword(1) dialogue sequence labeling  
Keyword(2) unsupervised domain adaptation  
Keyword(3) adversarial training  
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1st Author's Name Shota Orihashi  
1st Author's Affiliation NTT Corporation (NTT)
2nd Author's Name Naoki Makishima  
2nd Author's Affiliation NTT Corporation (NTT)
3rd Author's Name Mana Ihori  
3rd Author's Affiliation NTT Corporation (NTT)
4th Author's Name Akihiko Takashima  
4th Author's Affiliation NTT Corporation (NTT)
5th Author's Name Tomohiro Tanaka  
5th Author's Affiliation NTT Corporation (NTT)
6th Author's Name Ryo Masumura  
6th Author's Affiliation NTT Corporation (NTT)
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Speaker
Date Time 2020-09-10 15:25:00 
Presentation Time 25 
Registration for NLC 
Paper # IEICE-NLC2020-8 
Volume (vol) IEICE-120 
Number (no) no.166 
Page pp.34-39 
#Pages IEICE-6 
Date of Issue IEICE-NLC-2020-09-03 


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