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Paper Abstract and Keywords
Presentation 2015-07-16 17:50
Speaker Adaptation Technique for Speech Recognition using a Feature Augmentation Framework
Hiroshi Fujimura, Takashi Masuko (TOSHIBA) SP2015-42
Abstract (in Japanese) (See Japanese page) 
(in English) Deep Neural Networks (DNNs) are powerful machine learning models.Nevertheless, the performance degrades for out-of domain tasks. A popular approach is to use the adaptive training for avoiding the degradation. In particular, a rapid adaptation method is desired for many applications. However, rapid domain adaptation for DNNs with a small amount of data is difficult, due to a large number of parameters of the domain-dependent layer. In this paper, we propose a new adaptive training framework which can be used with a very small amount of adaptation data. An augmented features with domain-independent and domain-dependent components are input to a network with domain-dependent and domain-independent layers. The network is trained in an adaptive training scheme, and only domain weights are adjusted in the adaptation. Experiments on LVCSR tasks with male and female as domains are conducted, and significant improvements are obtained with only five utterances. Finally, out method obtained 0.46 point improvement from the baseline character error rate 19.95[%] using five utterances by the unsupervised adaptation in 4-fold cross validation test.
Keyword (in Japanese) (See Japanese page) 
(in English) Speech Recognition / Deep Neural Network / Adaptation / / / / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 146, SP2015-42, pp. 37-42, July 2015.
Paper # SP2015-42 
Date of Issue 2015-07-09 (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 SP2015-42

Conference Information
Committee SP IPSJ-SLP  
Conference Date 2015-07-16 - 2015-07-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Katakura Suwako Hotel 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Speech recognition and understanding, dialog system, etc. 
Paper Information
Registration To SP 
Conference Code 2015-07-SP-SLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Speaker Adaptation Technique for Speech Recognition using a Feature Augmentation Framework 
Sub Title (in English)  
Keyword(1) Speech Recognition  
Keyword(2) Deep Neural Network  
Keyword(3) Adaptation  
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1st Author's Name Hiroshi Fujimura  
1st Author's Affiliation TOSHIBA CORPORATION (TOSHIBA)
2nd Author's Name Takashi Masuko  
2nd Author's Affiliation TOSHIBA CORPORATION (TOSHIBA)
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Speaker Author-1 
Date Time 2015-07-16 17:50:00 
Presentation Time 30 minutes 
Registration for SP 
Paper # SP2015-42 
Volume (vol) vol.115 
Number (no) no.146 
Page pp.37-42 
#Pages 6 
Date of Issue 2015-07-09 (SP) 

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