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Paper Abstract and Keywords
Presentation 2010-06-17 16:45
Analysis on features and estimators for speech-based age estimation
Toshiya Wada, Takahiro Shinozaki, Sadaoki Furui (Tokyo Inst. of Tech.) SP2010-27
Abstract (in Japanese) (See Japanese page) 
(in English) Age estimation systems can be implemented using either a discrete classifier such as

support vector machine (SVM) or a continuous estimator such as support vector regression (SVR).

SVR is more popular than SVM in image processing area while on the other hand,

discrete classifier based systems have been mainly used in speech processing area.

Recently, SVR based age estimation systems using speech features have been proposed.

However, there has been no systematic comparison on these two approaches using speech features.

In this study, SVM and SVR based age estimation systems are compared using the same condition.

Several speech based features are investigated along with the two types of the estimators, including

maximum a posteori (MAP) adapted Gaussian mixture model (GMM) super vector

and our proposed maximum likelihood linear regression (MLLR) transform vector.

Experiments are performed using speech data from Corpus of Spontaneous Japanese (CSJ).

Experimental results show that SVR based estimator using MAP adapted GMM super vector features give the

highest estimation performance.
Keyword (in Japanese) (See Japanese page) 
(in English) age estimation / MLLR adaptation / support vector machine (SVM) / support vector regression (SVR) / Corpus of Spontaneous Japanese (CSJ) / / /  
Reference Info. IEICE Tech. Rep., vol. 110, no. 81, SP2010-27, pp. 31-36, June 2010.
Paper # SP2010-27 
Date of Issue 2010-06-10 (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 SP2010-27

Conference Information
Committee SP  
Conference Date 2010-06-17 - 2010-06-18 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyushu University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Speech/Language/Acoustic Education, etc. 
Paper Information
Registration To SP 
Conference Code 2010-06-SP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Analysis on features and estimators for speech-based age estimation 
Sub Title (in English)  
Keyword(1) age estimation  
Keyword(2) MLLR adaptation  
Keyword(3) support vector machine (SVM)  
Keyword(4) support vector regression (SVR)  
Keyword(5) Corpus of Spontaneous Japanese (CSJ)  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Toshiya Wada  
1st Author's Affiliation Tokyo Institute of Technology (Tokyo Inst. of Tech.)
2nd Author's Name Takahiro Shinozaki  
2nd Author's Affiliation Tokyo Institute of Technology (Tokyo Inst. of Tech.)
3rd Author's Name Sadaoki Furui  
3rd Author's Affiliation Tokyo Institute of Technology (Tokyo Inst. of Tech.)
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Speaker Author-1 
Date Time 2010-06-17 16:45:00 
Presentation Time 30 minutes 
Registration for SP 
Paper # SP2010-27 
Volume (vol) vol.110 
Number (no) no.81 
Page pp.31-36 
#Pages 6 
Date of Issue 2010-06-10 (SP) 

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