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 |
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) |
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SP2010-37 |
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) |
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Keyword(1) |
speech structure |
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CALL |
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regression |
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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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Speaker |
Author-1 |
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 |
6 |
Date of Issue |
2010-07-15 (SP) |
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