Paper Abstract and Keywords |
Presentation |
2012-07-19 14:30
Automatic pronunciation error detecting of Chinese using SVM with structural features Tongmu Zhao (Univ. of Tokyo), Akemi Hoshino (Toyama National College of Tech.), Masayuki Suzuki, Nobuaki Minematsu, Keikichi Hirose (Univ. of Tokyo) SP2012-50 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Pronunciation errors are often made by learners of a foreign language. To build a CALL (Computer-Aided Language Learning) system to support them, automatic error detection is an essential technique. In this study, Japanese learners of Chinese are focused on and automatic detection of their typical and frequent phoneme production errors is investigated. Due to difficulty of preparing labels of the phoneme errors found in real learners' data, we prepare native utterances including artificial phoneme errors. First, the target phonemes, which often appear to be problematic for Japanese learners to pronounce correctly, are defined through discussion with teachers. Then, phoneme production errors are created artificially by changing transcripts of native utterances and we further ask native speakers to read sentences with specific phoneme production errors. Three methods of GOP (Goodness of Pronunciation), LR (Likelihood Ratio), and SVM (Support Vector Machine) with struc-tural features are compared under the task of phoneme error detection. Here, GOP-based error detection is done by using the threshold optimized through development data. Results show that SVM with structural features performs better than both of the GOP-based and LR-based baseline methods. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
CALL / phoneme errors / error detection / Chinese / SVM / structural feature / GOP / likelihood ratio |
Reference Info. |
IEICE Tech. Rep., vol. 112, no. 141, SP2012-50, pp. 1-6, July 2012. |
Paper # |
SP2012-50 |
Date of Issue |
2012-07-12 (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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SP2012-50 |
Conference Information |
Committee |
SP IPSJ-SLP |
Conference Date |
2012-07-19 - 2012-07-21 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Hotel Takinoyu (Yamagata Pref.) |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Speech recognition, understanding, dialog, etc. |
Paper Information |
Registration To |
SP |
Conference Code |
2012-07-SP-SLP |
Language |
English (Japanese title is available) |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Automatic pronunciation error detecting of Chinese using SVM with structural features |
Sub Title (in English) |
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Keyword(1) |
CALL |
Keyword(2) |
phoneme errors |
Keyword(3) |
error detection |
Keyword(4) |
Chinese |
Keyword(5) |
SVM |
Keyword(6) |
structural feature |
Keyword(7) |
GOP |
Keyword(8) |
likelihood ratio |
1st Author's Name |
Tongmu Zhao |
1st Author's Affiliation |
The University of Tokyo (Univ. of Tokyo) |
2nd Author's Name |
Akemi Hoshino |
2nd Author's Affiliation |
Toyama National College of Technology (Toyama National College of Tech.) |
3rd Author's Name |
Masayuki Suzuki |
3rd Author's Affiliation |
The University of Tokyo (Univ. of Tokyo) |
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 |
2012-07-19 14:30:00 |
Presentation Time |
30 minutes |
Registration for |
SP |
Paper # |
SP2012-50 |
Volume (vol) |
vol.112 |
Number (no) |
no.141 |
Page |
pp.1-6 |
#Pages |
6 |
Date of Issue |
2012-07-12 (SP) |
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