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Paper Abstract and Keywords
Presentation 2010-07-22 14:20
Pronunciation assessment based on multilayer multiple regression analysis using structural features
Masayuki Suzuki, Ayano Nakamura (Univ. of Tokyo.), Yu Qiao (Shenzhen Institutes), Nobuaki Minematsu, Keikichi Hirose (Univ. of Tokyo.) SP2010-37
Abstract (in Japanese) (See Japanese page) 
(in English) In the rapid internationalization and informatization, many research efforts have been made to build computer-aided language learning (CALL) systems. Good pronunciation assessment systems should be built using the technologies which can deal with acoustic variabilities found in learners' utterances caused by non-linguistic factors such as age and gender. However, the widely-used acoustic modeling technique of HMM often shows unstable performances with speakers of different ages and genders. Recently, a new method of representing learners' pronunciations with their non-linguistic features effectively removed, called pronunciation structure. In this method, only the contrastive features of speech are extracted. However, the excessively high dimensionality of the structure comes to degrade its performance and, to solve this problem, multilayer regression analysis with structural features is proposed in this paper. The results show much higher correlation between human and machine performances of assessing learners' pronunciations compared to the previously proposed structure-based method. Further, the proposed method shows much higher robustness compared to the widely-used HMM-based method. In this paper, we also propose a good combination of the structure and the HMM.
Keyword (in Japanese) (See Japanese page) 
(in English) speech structure / CALL / regression / GOP / / / /  
Reference Info. IEICE Tech. Rep., vol. 110, no. 143, SP2010-37, pp. 13-18, July 2010.
Paper # SP2010-37 
Date of Issue 2010-07-15 (SP) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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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)
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Conference Information
Committee SP  
Conference Date 2010-07-22 - 2010-07-24 
Place (in Japanese) (See Japanese page) 
Place (in English) Ryokusui-tei (Sendai) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Recognition, Understanding, Dialogue, etc.(Prallelized with SIG-SLP) 
Paper Information
Registration To SP 
Conference Code 2010-07-SP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Pronunciation assessment based on multilayer multiple regression analysis using structural features 
Sub Title (in English)  
Keyword(1) speech structure  
Keyword(2) CALL  
Keyword(3) regression  
Keyword(4) GOP  
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1st Author's Name Masayuki Suzuki  
1st Author's Affiliation The University of Tokyo (Univ. of Tokyo.)
2nd Author's Name Ayano Nakamura  
2nd Author's Affiliation The University of Tokyo (Univ. of Tokyo.)
3rd Author's Name Yu Qiao  
3rd Author's Affiliation The Shenzhen Institutes of Advanced Technology (Shenzhen Institutes)
4th Author's Name Nobuaki Minematsu  
4th Author's Affiliation The University of Tokyo (Univ. of Tokyo.)
5th Author's Name Keikichi Hirose  
5th Author's Affiliation The University of Tokyo (Univ. of Tokyo.)
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Date Time 2010-07-22 14:20:00 
Presentation Time 25 minutes 
Registration for SP 
Paper # SP2010-37 
Volume (vol) vol.110 
Number (no) no.143 
Page pp.13-18 
#Pages
Date of Issue 2010-07-15 (SP) 


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