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Paper Abstract and Keywords
Presentation 2023-06-16 14:20
Study on Sign Language Recognition Using Deep Learning -- Recognition by conformer with the introduction of two-word sentences and sign language dictionary structure --
Kouki Ikeda, Tsutomu Kimura (National Institute of Technology,Toyota College) WIT2023-2
Abstract (in Japanese) (See Japanese page) 
(in English) This study aims to recognize words used in sentences in sign language recognition using machine learning. In order to train a sign language recognition model that takes into account the transitions that exist in a sign sentence, more sign sentence data is required. Therefore, we increase the amount of data by using two-word sentences instead of complete sign sentences, which are difficult to collect. The recognition model is based on Conformer, which has shown high performance in speech recognition, and it extracts global and local features of the signed sentences. Additionally, certain parameters from the Conformer, trained on signed words, are incorporated into the recognition model as a sign language dictionary to extract features specific to signed words. Furthermore, we utilize Connectionist Temporal Classification as the loss function for the recognition model. With these structures in place, we achieved a maximum recognition rate of approximately 79% on the Kimura Lab's sign language dataset. However, the recognition rate for complete sentences decreased as the number of learned words increased, indicating that the sign language dictionary structure was not fully utilized.
Keyword (in Japanese) (See Japanese page) 
(in English) Sign Language Recognition / Deep Learning / Connectionist Temporal Classification / Conformer / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 81, WIT2023-2, pp. 6-11, June 2023.
Paper # WIT2023-2 
Date of Issue 2023-06-09 (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 WIT2023-2

Conference Information
Committee WIT  
Conference Date 2023-06-16 - 2023-06-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Industry Support Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To WIT 
Conference Code 2023-06-WIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Study on Sign Language Recognition Using Deep Learning 
Sub Title (in English) Recognition by conformer with the introduction of two-word sentences and sign language dictionary structure 
Keyword(1) Sign Language Recognition  
Keyword(2) Deep Learning  
Keyword(3) Connectionist Temporal Classification  
Keyword(4) Conformer  
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1st Author's Name Kouki Ikeda  
1st Author's Affiliation National Institute of Technology,Toyota College (National Institute of Technology,Toyota College)
2nd Author's Name Tsutomu Kimura  
2nd Author's Affiliation National Institute of Technology,Toyota College (National Institute of Technology,Toyota College)
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Speaker Author-1 
Date Time 2023-06-16 14:20:00 
Presentation Time 25 minutes 
Registration for WIT 
Paper # WIT2023-2 
Volume (vol) vol.123 
Number (no) no.81 
Page pp.6-11 
#Pages 6 
Date of Issue 2023-06-09 (WIT) 

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