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Paper Abstract and Keywords
Presentation 2015-03-03 10:45
[Poster Presentation] Automatic Language Identification Based on Posterior Probability on Articulatory Classes -- Language-Independent Articulatory Feature Extractor and Codebook Size --
Takumi Hirata, Kazuyuki Takagi (UEC) EA2014-106 SIP2014-147 SP2014-169
Abstract (in Japanese) (See Japanese page) 
(in English) The language identification method is presented that utilizes information on sequential pattern of posterior probabilities of articulatory classes, which are defined based on International Phonetic Alphabet. The present method calculates log posterior probability of each defined articulatory class on speech spectrum to form a multi-dimensional articulatory feature (AF) vector, then vector quantizes it. Statistics on the sequence of the VQ code is modeled with n-gram language model, which is used to estimate likelihoods of the target languages for input VQ code sequences; the language of the model giving the largest likelihood is identified as the input speech language. This paper shows that sequential pattern of posterior probabilities of articulatory classes is effective for language identification, and compares the performance of the method with the language-dependent AF extractors and the one with the language-independent AF extractor. The language identification experiments between Japanese and English were conducted. The results show that the optimum identification rate of 98.1% was obtained with relatively small VQ size of 64 with the language-dependent AF extractors while the VQ size for optimal identification rate of 95.6% was 256 with the language-independent AF extractor.
Keyword (in Japanese) (See Japanese page) 
(in English) language identification / phonological discrimination feature / articulatory class / posterior probability / International Phonetic Alphabet / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 475, SP2014-169, pp. 187-190, March 2015.
Paper # SP2014-169 
Date of Issue 2015-02-23 (EA, SIP, 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)
Download PDF EA2014-106 SIP2014-147 SP2014-169

Conference Information
Committee SIP EA SP  
Conference Date 2015-03-02 - 2015-03-03 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To SP 
Conference Code 2015-03-SIP-EA-SP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automatic Language Identification Based on Posterior Probability on Articulatory Classes 
Sub Title (in English) Language-Independent Articulatory Feature Extractor and Codebook Size 
Keyword(1) language identification  
Keyword(2) phonological discrimination feature  
Keyword(3) articulatory class  
Keyword(4) posterior probability  
Keyword(5) International Phonetic Alphabet  
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1st Author's Name Takumi Hirata  
1st Author's Affiliation The University of Electro-Communications (UEC)
2nd Author's Name Kazuyuki Takagi  
2nd Author's Affiliation The University of Electro-Communications (UEC)
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Date Time 2015-03-03 10:45:00 
Presentation Time 90 minutes 
Registration for SP 
Paper # EA2014-106, SIP2014-147, SP2014-169 
Volume (vol) vol.114 
Number (no) no.473(EA), no.474(SIP), no.475(SP) 
Page pp.187-190 
#Pages
Date of Issue 2015-02-23 (EA, SIP, SP) 


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