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Paper Abstract and Keywords
Presentation 2017-07-27 16:15
Voice Conversion Using Sequence-to-Sequence Learning of Context Posterior Probabilities and Evaluation of Dual Learning
Hiroyuki Miyoshi, Yuki Saito, Shinnosuke Takamichi, Hiroshi Saruwatari (Univ. of Tokyo) SP2017-17
Abstract (in Japanese) (See Japanese page) 
(in English) Voice conversion (VC) using sequence-to-sequence learning of context posterior probabilities is proposed. Conventional VC using shared context posterior probabilities predicts target speech parameters from the context posterior probabilities estimated from the source speech parameters. Although conventional VC can be built from non-parallel data, it is difficult to convert speaker individuality such as phonetic property and speaking rate contained in the posterior probabilities because the source posterior probabilities are directly used for predicting target speech parameters. In this work, we assume that the training data partly include parallel speech data and propose sequence-to-sequence learning between the source and target posterior probabilities. The conversion models perform non-linear and variable-length transformation from the source probability sequence to the target one. Further, we propose a joint training algorithm for the modules. In contrast to conventional VC, which separately trains the speech recognition that estimates posterior probabilities and the speech synthesis that predicts target speech parameters, our proposed method jointly trains these modules along with the proposed probability conversion modules. Experimental results demonstrate that our approach outperforms the conventional VC.
Keyword (in Japanese) (See Japanese page) 
(in English) voice conversion / context posterior probabilities / sequence-to-sequence learning / dual learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 160, SP2017-17, pp. 9-14, July 2017.
Paper # SP2017-17 
Date of Issue 2017-07-20 (SP) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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)
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Conference Information
Committee SP IPSJ-SLP  
Conference Date 2017-07-27 - 2017-07-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Akiu Resort Hotel Crescent 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Speech recognition and understanding, dialog system, etc. 
Paper Information
Registration To SP 
Conference Code 2017-07-SP-SLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Voice Conversion Using Sequence-to-Sequence Learning of Context Posterior Probabilities and Evaluation of Dual Learning 
Sub Title (in English)  
Keyword(1) voice conversion  
Keyword(2) context posterior probabilities  
Keyword(3) sequence-to-sequence learning  
Keyword(4) dual learning  
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1st Author's Name Hiroyuki Miyoshi  
1st Author's Affiliation The University of Tokyo (Univ. of Tokyo)
2nd Author's Name Yuki Saito  
2nd Author's Affiliation The University of Tokyo (Univ. of Tokyo)
3rd Author's Name Shinnosuke Takamichi  
3rd Author's Affiliation The University of Tokyo (Univ. of Tokyo)
4th Author's Name Hiroshi Saruwatari  
4th Author's Affiliation The University of Tokyo (Univ. of Tokyo)
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Date Time 2017-07-27 16:15:00 
Presentation Time 30 minutes 
Registration for SP 
Paper # SP2017-17 
Volume (vol) vol.117 
Number (no) no.160 
Page pp.9-14 
#Pages
Date of Issue 2017-07-20 (SP) 


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