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Paper Abstract and Keywords
Presentation 2018-09-14 13:00
A Study on Interaction Analysis Using Japanese Learner's Conversation Data and the Tendency of Dialogue Breaking
Hiromitsu Ota (OUJ) DE2018-9
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, the introduction of chat bots to call centers and the like has become popular, more accurate, dialogue response with less breakdown is required. On the other hand, in the field of natural language processing using deep learning, expression learning such as word 2 vec spreads, the responses and utterances between utterances are emphasized and challenged. Therefore, we examined application of qualitative mutual action framework in sociology's ethnomethodology and conversation analysis. We examined effectiveness by using the Japanese language learner conversation data of the National Institute of Japanese Language and examined the characteristics of dialog crash and the applicability of automatic dialogue generation.
Keyword (in Japanese) (See Japanese page) 
(in English) chatbot / Seq2Seq / word2vec / automatic dialogue generation / Ethnomethodology / conversation analysis / Dialogue collapse / Dialogue response  
Reference Info. IEICE Tech. Rep., vol. 118, no. 213, DE2018-9, pp. 1-6, Sept. 2018.
Paper # DE2018-9 
Date of Issue 2018-09-05 (DE) 
ISSN 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)
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Conference Information
Committee DE IPSJ-DBS IPSJ-IFAT  
Conference Date 2018-09-12 - 2018-09-14 
Place (in Japanese) (See Japanese page) 
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Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To DE 
Conference Code 2018-09-DE-DBS-IFAT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Interaction Analysis Using Japanese Learner's Conversation Data and the Tendency of Dialogue Breaking 
Sub Title (in English)  
Keyword(1) chatbot  
Keyword(2) Seq2Seq  
Keyword(3) word2vec  
Keyword(4) automatic dialogue generation  
Keyword(5) Ethnomethodology  
Keyword(6) conversation analysis  
Keyword(7) Dialogue collapse  
Keyword(8) Dialogue response  
1st Author's Name Hiromitsu Ota  
1st Author's Affiliation The Open University of Japan (OUJ)
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Speaker Author-1 
Date Time 2018-09-14 13:00:00 
Presentation Time 30 minutes 
Registration for DE 
Paper # DE2018-9 
Volume (vol) vol.118 
Number (no) no.213 
Page pp.1-6 
#Pages
Date of Issue 2018-09-05 (DE) 


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