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Paper Abstract and Keywords
Presentation 2024-03-10 10:50
Quality Assessment for debate using combined models and data augmentation
Shunsuke Hashiguchi, Kazutaka Shimada (KIT) NLC2023-23
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, the incorporation of group debates has emerged as a strategic approach for measuring communication ability within the realms of entrance and employment examinations. However, the equitable evaluation of debates for such kinds of examinations proves challenging. Therefore, a system is required to assess debates appropriately. In this study, we work on the quality assessment of debates focused on the Japanese language. The studies related to debate primarily focused on English, while those targeted at Japanese are limited. Consequently, the availability of debate data in Japanese is more constrained compared to English. To handle the low-resource data, we propose two methods: the utilization of a dialogue-specific model and data augmentation using GPT-4. We demonstrate that employing a dialogue-specific model does not yield statistically significant scores, while data augmentation using GPT-4 enhances the performance.
Keyword (in Japanese) (See Japanese page) 
(in English) debate / quality assessment / dialogue-specific model / GPT-4 / pseudo data / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 416, NLC2023-23, pp. 1-6, March 2024.
Paper # NLC2023-23 
Date of Issue 2024-03-03 (NLC) 
ISSN 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 NLC2023-23

Conference Information
Committee NLC IPSJ-NL  
Conference Date 2024-03-10 - 2024-03-11 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) Applications of natural language processing, and etc. 
Paper Information
Registration To NLC 
Conference Code 2024-03-NLC-NL 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Quality Assessment for debate using combined models and data augmentation 
Sub Title (in English)  
Keyword(1) debate  
Keyword(2) quality assessment  
Keyword(3) dialogue-specific model  
Keyword(4) GPT-4  
Keyword(5) pseudo data  
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Keyword(8)  
1st Author's Name Shunsuke Hashiguchi  
1st Author's Affiliation Kyushu Institute of Technology (KIT)
2nd Author's Name Kazutaka Shimada  
2nd Author's Affiliation Kyushu Institute of Technology (KIT)
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Speaker Author-1 
Date Time 2024-03-10 10:50:00 
Presentation Time 25 minutes 
Registration for NLC 
Paper # NLC2023-23 
Volume (vol) vol.123 
Number (no) no.416 
Page pp.1-6 
#Pages 6 
Date of Issue 2024-03-03 (NLC) 

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