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Paper Abstract and Keywords
Presentation 2018-01-21 16:00
A study on voice conversion based on WaveNet
Jumpei Niwa, Takenori Yoshimura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda (NIT) SP2017-84
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes a voice conversion technique based on WaveNet to directly generate target audio waveforms from acoustic features of a source speaker. In voice conversion based on statistical models, the relation between acoustic features, e.g., spectral parameters, extracted from source and target audio waveforms is modeled by statistical models, such as Gaussian mixture models and neural networks. Although modeling the relation between acoustic features is reasonable and efficient, the model is not optimized for predicting target audio waveforms because the vocoder parameters are used as the intermediate representations of audio waveforms. To overcome this problem, the relation between target audio waveforms and acoustic features extracted from source audio waveforms is modeled by using WaveNet, which is a generative model for audio waveforms, in the proposed method. Therefore, the proposed model can directly generate converted audio waveforms without vocoders. Experimental results indicate that the proposed method improves the naturalness and the speaker similarity of the converted speech from a conventional DNN-based method, and these results clearly show the effectiveness of the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) voice conversion / WaveNet / DNN / statistical model / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 393, SP2017-84, pp. 99-104, Jan. 2018.
Paper # SP2017-84 
Date of Issue 2018-01-13 (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 SP2017-84

Conference Information
Committee SP ASJ-H  
Conference Date 2018-01-20 - 2018-01-21 
Place (in Japanese) (See Japanese page) 
Place (in English) The University of Tokyo 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SP 
Conference Code 2018-01-SP-H 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A study on voice conversion based on WaveNet 
Sub Title (in English)  
Keyword(1) voice conversion  
Keyword(2) WaveNet  
Keyword(3) DNN  
Keyword(4) statistical model  
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1st Author's Name Jumpei Niwa  
1st Author's Affiliation Nagoya Institute of Technology (NIT)
2nd Author's Name Takenori Yoshimura  
2nd Author's Affiliation Nagoya Institute of Technology (NIT)
3rd Author's Name Kei Hashimoto  
3rd Author's Affiliation Nagoya Institute of Technology (NIT)
4th Author's Name Keiichiro Oura  
4th Author's Affiliation Nagoya Institute of Technology (NIT)
5th Author's Name Yoshihiko Nankaku  
5th Author's Affiliation Nagoya Institute of Technology (NIT)
6th Author's Name Keiichi Tokuda  
6th Author's Affiliation Nagoya Institute of Technology (NIT)
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Speaker Author-1 
Date Time 2018-01-21 16:00:00 
Presentation Time 25 minutes 
Registration for SP 
Paper # SP2017-84 
Volume (vol) vol.117 
Number (no) no.393 
Page pp.99-104 
#Pages 6 
Date of Issue 2018-01-13 (SP) 

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