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Paper Abstract and Keywords
Presentation 2026-07-04 11:30
Continuous Sign Language Recognition via Synthetic Data Augmentation from Isolated Signs
Kenta Suzuki, Tsutomu Kimura (NITTC), Kazuyuki Kanda (TOPSL) WIT2026-4
Abstract (in Japanese) (See Japanese page) 
(in English) A lack of training data, caused by the high cost of data collection and privacy concerns regarding signers′ identities, poses a significant challenge in the practical implementation of continuous sign language recognition. In this study, we propose a method to augment training data by artificially synthesizing continuous sign language sequences from existing isolated sign videos using keypoint coordinates. Training a Transformer model with the synthesized data, which incorporates easing function-based interpolation between signs and dynamic data augmentation, resulted in a substantial improvement in recognition accuracy. Furthermore, we confirmed characteristics such as a plateau in accuracy as vocabulary size and data volume increased, as well as error tendencies specific to the autoregressive model.
Keyword (in Japanese) (See Japanese page) 
(in English) Continuous Sign Language Recognition / Data Augmentation / Synthetic Data / Keypoint Coordinates / / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 93, WIT2026-4, pp. 19-24, July 2026.
Paper # WIT2026-4 
Date of Issue 2026-06-27 (WIT) 
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 WIT2026-4

Conference Information
Committee WIT  
Conference Date 2026-07-04 - 2026-07-04 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To WIT 
Conference Code 2026-07-WIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Continuous Sign Language Recognition via Synthetic Data Augmentation from Isolated Signs 
Sub Title (in English)  
Keyword(1) Continuous Sign Language Recognition  
Keyword(2) Data Augmentation  
Keyword(3) Synthetic Data  
Keyword(4) Keypoint Coordinates  
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1st Author's Name Kenta Suzuki  
1st Author's Affiliation National Institute of Technology (KOSEN), Toyota College (NITTC)
2nd Author's Name Tsutomu Kimura  
2nd Author's Affiliation National Institute of Technology (KOSEN), Toyota College (NITTC)
3rd Author's Name Kazuyuki Kanda  
3rd Author's Affiliation Testing Organization for Sign Language Proficiency (TOPSL)
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Speaker Author-1 
Date Time 2026-07-04 11:30:00 
Presentation Time 25 minutes 
Registration for WIT 
Paper # WIT2026-4 
Volume (vol) vol.126 
Number (no) no.93 
Page pp.19-24 
#Pages 6 
Date of Issue 2026-06-27 (WIT) 

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