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Paper Abstract and Keywords
Presentation 2012-02-09 15:15
Electrooculogram recognition using hidden Markov model
Fuming Fang, Takahiro Shinozaki, Yasuo Horiuchi, Shingo Kuroiwa (Chiba Univ), Sadaoki Furui (Tokyo Tech), Toshimitsu Musha (BFL) PRMU2011-202 SP2011-117
Abstract (in Japanese) (See Japanese page) 
(in English) In order to provide an efficient means of communication for those who cannot move muscles of their whole body except eyes due to amyotrophic lateral sclerosis (ALS), we propose an speech synthesis interface based on electrooculogram (EOG) input. The system consists of EOG electrodes, an EOG recognition system, and a speech synthesis system. In this paper, we report experiments about the EOG recognition system that we have developed borrowing speech recognition techniques using hidden Markov model (HMM). In the experiments, we first make user-dependent EOG recognition systems. It is shown that the systems give 95.7% recognition accuracy on average. While they give high recognition performance, a problem is that they need a large amount of user-specific data for model training. From the application point of view, user-independent systems are more preferable. As the second experiment, we evaluate the effect of individual differences in EOG recognition. It is shown that the recognition accuracy largely drops if there is a mismatch between EOG model and recognition data. As the last experiment, we apply speaker adaptation techniques that had been developed for speech recognition to EOG recognition, and show that they are effective to improve EOG recognition accuracy.
Keyword (in Japanese) (See Japanese page) 
(in English) Electrooculogram / Hidden Markov model / Recognition / Speech synthesis / Information assurance / / /  
Reference Info. IEICE Tech. Rep., vol. 111, no. 430, PRMU2011-202, pp. 97-102, Feb. 2012.
Paper # PRMU2011-202 
Date of Issue 2012-02-02 (PRMU, SP) 
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)
Download PDF PRMU2011-202 SP2011-117

Conference Information
Committee PRMU SP  
Conference Date 2012-02-09 - 2012-02-10 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2012-02-PRMU-SP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Electrooculogram recognition using hidden Markov model 
Sub Title (in English)  
Keyword(1) Electrooculogram  
Keyword(2) Hidden Markov model  
Keyword(3) Recognition  
Keyword(4) Speech synthesis  
Keyword(5) Information assurance  
Keyword(6)  
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Keyword(8)  
1st Author's Name Fuming Fang  
1st Author's Affiliation Chiba University (Chiba Univ)
2nd Author's Name Takahiro Shinozaki  
2nd Author's Affiliation Chiba University (Chiba Univ)
3rd Author's Name Yasuo Horiuchi  
3rd Author's Affiliation Chiba University (Chiba Univ)
4th Author's Name Shingo Kuroiwa  
4th Author's Affiliation Chiba University (Chiba Univ)
5th Author's Name Sadaoki Furui  
5th Author's Affiliation Tokyo Institute of Technology (Tokyo Tech)
6th Author's Name Toshimitsu Musha  
6th Author's Affiliation Brain Functions Laboratory,Inc (BFL)
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Speaker Author-1 
Date Time 2012-02-09 15:15:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2011-202, SP2011-117 
Volume (vol) vol.111 
Number (no) no.430(PRMU), no.431(SP) 
Page pp.97-102 
#Pages 6 
Date of Issue 2012-02-02 (PRMU, SP) 

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