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Paper Abstract and Keywords
Presentation 2015-06-18 16:00
Noise-robust Prediction of Pronunciation Distances Aiming at Clustering of World Englishes Using a Learner's Self-centered Viewpoint
Yuichi Sato, Yosuke Kashiwagi, Shun Kasahara, Nobuaki Minematsu, Daisuke Saito, Keikichi Hirose (UT) PRMU2015-45 SP2015-14 WIT2015-14
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years,we have more and more international tourists and in 2020, we have Tokyo Olympic Games. For communicating with those tourists, the default language is English but they speak English with various accents. To realize smooth communication with these tourists, we are developing a technical infrastructure to accustom Japanese people to variously accented Englishes (World Englishes). The infrastructure aims at clustering a large diversity of English pronunciations on an individual basis and visualizing the diversity in an educationally effective way. For clustering, a technique is needed that can predict the accent gap between any speaker pair and we developed it by integrating pronunciation structure analysis and support vector regression. In this paper, the prediction performance is evaluated when the prediction technique is applied for visualization using a user's self-centered viewpoint and when it is applied with a noise suppression technique. Results show that the performance is comparable to that observed when we use phonemic, not phonetic, transcripts and that 10 [dB] is enough as SNR to guarantee the prediction performance realized in a clean condition.
Keyword (in Japanese) (See Japanese page) 
(in English) World Englishes / pronunciation clustering / structural representation / support vector regression / self-centered visualization / noise suppression / DNN /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 99, SP2015-14, pp. 77-82, June 2015.
Paper # SP2015-14 
Date of Issue 2015-06-11 (PRMU, SP, WIT) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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 PRMU2015-45 SP2015-14 WIT2015-14

Conference Information
Committee WIT SP ASJ-H PRMU  
Conference Date 2015-06-18 - 2015-06-19 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SP 
Conference Code 2015-06-WIT-SP-H-PRMU 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Noise-robust Prediction of Pronunciation Distances Aiming at Clustering of World Englishes Using a Learner's Self-centered Viewpoint 
Sub Title (in English)  
Keyword(1) World Englishes  
Keyword(2) pronunciation clustering  
Keyword(3) structural representation  
Keyword(4) support vector regression  
Keyword(5) self-centered visualization  
Keyword(6) noise suppression  
Keyword(7) DNN  
Keyword(8)  
1st Author's Name Yuichi Sato  
1st Author's Affiliation The University of Tokyo (UT)
2nd Author's Name Yosuke Kashiwagi  
2nd Author's Affiliation The University of Tokyo (UT)
3rd Author's Name Shun Kasahara  
3rd Author's Affiliation The University of Tokyo (UT)
4th Author's Name Nobuaki Minematsu  
4th Author's Affiliation The University of Tokyo (UT)
5th Author's Name Daisuke Saito  
5th Author's Affiliation The University of Tokyo (UT)
6th Author's Name Keikichi Hirose  
6th Author's Affiliation The University of Tokyo (UT)
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Speaker Author-1 
Date Time 2015-06-18 16:00:00 
Presentation Time 25 minutes 
Registration for SP 
Paper # PRMU2015-45, SP2015-14, WIT2015-14 
Volume (vol) vol.115 
Number (no) no.98(PRMU), no.99(SP), no.100(WIT) 
Page pp.77-82 
#Pages
Date of Issue 2015-06-11 (PRMU, SP, WIT) 


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