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Paper Abstract and Keywords
Presentation 2017-08-28 16:10
Improvement and Evaluation of a Machine Translation System from Japanese Texts to Sign Language CG Animations for Weather News
Naoto Kato, Taro Miyazaki (NHK), Seiki Inoue (NHK-MT), Tsubasa Uchida, Makiko Azuma, Shuichi Umeda, Yuko Yamanouchi, Hideki Sumiyoshi (NHK), Nobuyuki Hiruma (NHK-ES), Yuji Nagashima (Kogakuin Univ.) WIT2017-19
Abstract (in Japanese) (See Japanese page) 
(in English) We have been developing a machine translation system from Japanese texts to Japanese Sign Language (JSL) CG animations for weather news. To overcome some problems of the initially-developed machine translation system, we improved the system by increasing our JSL corpus size, developing our new translation method, introducing clause-based and phrase-based CG animations, producing a new CG avatar, adding facial expressions to the avatar and synthesizing mouth patterns. We conducted a series of experiments for the improved system and obtained an accuracy increase from 3.4 to 4.0 in 5 grade evaluation. Furthermore, we found the improved system has less number of claims pointed by the evaluators than our initially-developed system.
Keyword (in Japanese) (See Japanese page) 
(in English) Sign Language / Japanese / Machine Translation / Corpus / Computer Graphics / Weather News / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 188, WIT2017-19, pp. 27-32, Aug. 2017.
Paper # WIT2017-19 
Date of Issue 2017-08-21 (WIT) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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 WIT  
Conference Date 2017-08-28 - 2017-08-29 
Place (in Japanese) (See Japanese page) 
Place (in English) Faculty of Engineering Science, Akita Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Well-being Information Technology, etc. 
Paper Information
Registration To WIT 
Conference Code 2017-08-WIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Improvement and Evaluation of a Machine Translation System from Japanese Texts to Sign Language CG Animations for Weather News 
Sub Title (in English)  
Keyword(1) Sign Language  
Keyword(2) Japanese  
Keyword(3) Machine Translation  
Keyword(4) Corpus  
Keyword(5) Computer Graphics  
Keyword(6) Weather News  
Keyword(7)  
Keyword(8)  
1st Author's Name Naoto Kato  
1st Author's Affiliation NHK Science and Technology Research Laboratories (NHK)
2nd Author's Name Taro Miyazaki  
2nd Author's Affiliation NHK Science and Technology Research Laboratories (NHK)
3rd Author's Name Seiki Inoue  
3rd Author's Affiliation NHK Media Technology, Inc. (NHK-MT)
4th Author's Name Tsubasa Uchida  
4th Author's Affiliation NHK Science and Technology Research Laboratories (NHK)
5th Author's Name Makiko Azuma  
5th Author's Affiliation NHK Science and Technology Research Laboratories (NHK)
6th Author's Name Shuichi Umeda  
6th Author's Affiliation NHK Science and Technology Research Laboratories (NHK)
7th Author's Name Yuko Yamanouchi  
7th Author's Affiliation NHK Science and Technology Research Laboratories (NHK)
8th Author's Name Hideki Sumiyoshi  
8th Author's Affiliation NHK Science and Technology Research Laboratories (NHK)
9th Author's Name Nobuyuki Hiruma  
9th Author's Affiliation NHK Engineering System, Inc. (NHK-ES)
10th Author's Name Yuji Nagashima  
10th Author's Affiliation Kogakuin University (Kogakuin Univ.)
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Speaker Author-1 
Date Time 2017-08-28 16:10:00 
Presentation Time 25 minutes 
Registration for WIT 
Paper # WIT2017-19 
Volume (vol) vol.117 
Number (no) no.188 
Page pp.27-32 
#Pages
Date of Issue 2017-08-21 (WIT) 


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