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Paper Abstract and Keywords
Presentation 2017-10-20 10:40
Low Cost Semi-automatic Correction and Adaptation Method Assuming Automatic Captioning System for Lectures
Tamiya Kenta, Terada Yuji, Kai Atsuhiko (Shizuoka Univ.) SP2017-50 WIT2017-46
Abstract (in Japanese) (See Japanese page) 
(in English) By using Automatic Speech Recognition (ASR) technology, it is possible to subtitle lecture and other voices at low cost and in real time, which is a great help for the hearing impaired people. However, when using the ASR system, there is a problem that the recognition accuracy is greatly influenced by the fact that the technical term tends to become an unknown word especially in a university lecture and the recognition accuracy is greatly influenced by the speaker and the recording environment. In order to correct such a misrecognition result, conventional semi-automatic captioning systems require several operators for simultaneous editing, or cause a large delay for time-consuming editing work. In this paper, we propose a low cost correction method to feedback only a part of errors such as misrecognized technical terms and to identify and correct erroneously recognized segments by using Spoken Term Detection (STD) and lattice modification methods. We also adopt an unsupervised language model adaptation for additional subtitle correction after the modified online caption text were obtained for a lecture. We report the experimental result of our proposed system using the lecture speech corpus.
Keyword (in Japanese) (See Japanese page) 
(in English) Automatic Speech Recognition / Spoken Term Detection / Automatic captioning system / Recognition error correction / Supporting hearing impaired / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 250, SP2017-50, pp. 89-94, Oct. 2017.
Paper # SP2017-50 
Date of Issue 2017-10-12 (SP, WIT) 
ISSN Print edition: ISSN 0913-5685    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)
Notes on Review This article is a technical report without peer review, and its polished version will be published elsewhere.
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Conference Information
Committee WIT SP  
Conference Date 2017-10-19 - 2017-10-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Tobata Library of Kyutech (Kitakyushu) 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SP 
Conference Code 2017-10-WIT-SP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Low Cost Semi-automatic Correction and Adaptation Method Assuming Automatic Captioning System for Lectures 
Sub Title (in English)  
Keyword(1) Automatic Speech Recognition  
Keyword(2) Spoken Term Detection  
Keyword(3) Automatic captioning system  
Keyword(4) Recognition error correction  
Keyword(5) Supporting hearing impaired  
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1st Author's Name Tamiya Kenta  
1st Author's Affiliation Shizuoka University (Shizuoka Univ.)
2nd Author's Name Terada Yuji  
2nd Author's Affiliation Shizuoka University (Shizuoka Univ.)
3rd Author's Name Kai Atsuhiko  
3rd Author's Affiliation Shizuoka University (Shizuoka Univ.)
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Speaker Author-1 
Date Time 2017-10-20 10:40:00 
Presentation Time 20 minutes 
Registration for SP 
Paper # SP2017-50, WIT2017-46 
Volume (vol) vol.117 
Number (no) no.250(SP), no.251(WIT) 
Page pp.89-94 
#Pages
Date of Issue 2017-10-12 (SP, WIT) 


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