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Paper Abstract and Keywords
Presentation 2009-01-30 14:40
Mixture of Probabilistic Linear Regression for Voice Conversion
Yu Qiao, Daisuke Saito, Nobuaki Minematsu (Univ. of Tokyo) SP2008-139
Abstract (in Japanese) (See Japanese page) 
(in English) This paper introduces a model of Mixture of Probabilistic Linear Regressions (MPLR) to learn a mapping function between two feature spaces. The MPLR consists of weighted combination of several probabilistic linear regressions, whose parameters are estimated by using matrix calculation. The mixture nature of MPLR allows it to model nonlinear transformation. The formulation of MPLR is general and independent of the types of the density models used. Two well-known GMM-based mapping methods for voice conversion [1], [2] can be regarded as the special cases of MPLR. This unifed view not only provides insights to the GMM-based mapping techniques, but also indicates methods to improve them. Compared to [1], our formulation of MPLR avoids solving complex linear equations and yields a faster estimation of the transform parameters. As for [2], the MPLR estimation provides a modifed mapping function which overcomes an implicit problem in [2]'s mapping function. We carried out experiments to compare the MPLR-based methods with the traditional GMM-based methods [1], [2] on a voice conversion task. The experimental results show that the MPLR-based methods always have better performance in various parameter setups.
Keyword (in Japanese) (See Japanese page) 
(in English) Space mapping / non-linear transform / mixture model / linear regression / voice conversion / / /  
Reference Info. IEICE Tech. Rep., vol. 108, no. 422, SP2008-139, pp. 79-84, Jan. 2009.
Paper # SP2008-139 
Date of Issue 2009-01-22 (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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Conference Information
Committee SP  
Conference Date 2009-01-29 - 2009-01-30 
Place (in Japanese) (See Japanese page) 
Place (in English) NAIST 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SP 
Conference Code 2009-01-SP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Mixture of Probabilistic Linear Regression for Voice Conversion 
Sub Title (in English)  
Keyword(1) Space mapping  
Keyword(2) non-linear transform  
Keyword(3) mixture model  
Keyword(4) linear regression  
Keyword(5) voice conversion  
Keyword(6)  
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Keyword(8)  
1st Author's Name Yu Qiao  
1st Author's Affiliation The University of Tokyo (Univ. of Tokyo)
2nd Author's Name Daisuke Saito  
2nd Author's Affiliation The University of Tokyo (Univ. of Tokyo)
3rd Author's Name Nobuaki Minematsu  
3rd Author's Affiliation The University of Tokyo (Univ. of Tokyo)
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Speaker Author-1 
Date Time 2009-01-30 14:40:00 
Presentation Time 25 minutes 
Registration for SP 
Paper # SP2008-139 
Volume (vol) vol.108 
Number (no) no.422 
Page pp.79-84 
#Pages 6 
Date of Issue 2009-01-22 (SP) 

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