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Paper Abstract and Keywords
Presentation 2014-12-16 13:30
[Poster Presentation] Automatic Language Identification Based on Posterior Probability on Articulatory Classes
Takumi Hirata, Kazuyuki Takagi (UEC) SP2014-125
Abstract (in Japanese) (See Japanese page) 
(in English) Extraction of features from input speech that are effective in distinguishing the language is a key issue for language identification system. We use posterior probabilities on articulatory classes as features for language identification. Posterior probability on each articulatory class is calculated by GMMs. Each GMM is trained with MFCC data of speech segments labeled with the phonemes or acoustic events that correspond to the articulatory class. The posterior probability values of the articulatory classes are concatenated to form an articulatory-feature-class-posterior-probability (AFCPP) vector at each analysis frame. These vectors are then quantized to yield VQ code sequence, which is used as the training data for a n-gram language model. Language identification is performed by selecting the n-gram model that yields the highest likelihood for the AFCPP vector sequence of the input utterance. Language identification experiment between Japanese and English by the present method showed identification rate of 97.1%.
Keyword (in Japanese) (See Japanese page) 
(in English) language identification / articulatory class / posterior probability / International Phonetic Alphabet / / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 365, SP2014-125, pp. 153-157, Dec. 2014.
Paper # SP2014-125 
Date of Issue 2014-12-08 (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)
Download PDF SP2014-125

Conference Information
Committee NLC IPSJ-NL SP IPSJ-SLP JSAI-SLUD  
Conference Date 2014-12-15 - 2014-12-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Tokyo Institute of Technology (Suzukakedai Campus) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) The 6th Symposium on Collective Knowlege 
Paper Information
Registration To SP 
Conference Code 2014-12-NLC-NL-SP-SLP-SLUD 
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)  
Keyword(1) language identification  
Keyword(2) articulatory class  
Keyword(3) posterior probability  
Keyword(4) 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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Speaker Author-1 
Date Time 2014-12-16 13:30:00 
Presentation Time 90 minutes 
Registration for SP 
Paper # SP2014-125 
Volume (vol) vol.114 
Number (no) no.365 
Page pp.153-157 
#Pages 5 
Date of Issue 2014-12-08 (SP) 

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