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Paper Abstract and Keywords
Presentation 2017-01-21 11:00
[Poster Presentation] A Study on Singer-Independent Singing Voice Conversion Using Read Speech Based on Neural Network
Harunori Koike, Takashi Nose, Akinori Ito (Tohoku Univ.) SP2016-67
Abstract (in Japanese) (See Japanese page) 
(in English) There is a problem that the conventional method requires the speech of the source speaker for training. We proposed a method of voice conversion by which voice of an arbitrary input speaker can be converted closer to that of the specified target speaker using a neural network for many-to-one mapping between multiple source speakers and a target speaker to solve the problem. Furthermore, we can obtain more natural converted speech by using spectral differential filter. In this study, we evaluated the performance of conversion by read speech. Considering the application to karaoke, it is necessary to consider conversion of singing voice as well. It is ideal to use singing voice for training neural network, but it is extremely expensive to use parallel singing voice of a large number of singers. Therefore, in this paper, we study the singer-independent singing voice conversion based on a neural network using read speech for trainning. Evaluation experiments show that we can obtain more natural converted speech than singer-dependent method using singing voice and can perform many-to-one conversion from multiple singers to a single target singer.
Keyword (in Japanese) (See Japanese page) 
(in English) singing voice conversion / neural network / singer-independent conversion / spectral differential filter / read speech / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 414, SP2016-67, pp. 17-22, Jan. 2017.
Paper # SP2016-67 
Date of Issue 2017-01-14 (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 2017-01-21 - 2017-01-21 
Place (in Japanese) (See Japanese page) 
Place (in English) The University of Tokyo 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Synthesis, Generation, Prosody, etc. 
Paper Information
Registration To SP 
Conference Code 2017-01-SP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Singer-Independent Singing Voice Conversion Using Read Speech Based on Neural Network 
Sub Title (in English)  
Keyword(1) singing voice conversion  
Keyword(2) neural network  
Keyword(3) singer-independent conversion  
Keyword(4) spectral differential filter  
Keyword(5) read speech  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Harunori Koike  
1st Author's Affiliation Tohoku University (Tohoku Univ.)
2nd Author's Name Takashi Nose  
2nd Author's Affiliation Tohoku University (Tohoku Univ.)
3rd Author's Name Akinori Ito  
3rd Author's Affiliation Tohoku University (Tohoku Univ.)
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Speaker Author-1 
Date Time 2017-01-21 11:00:00 
Presentation Time 60 minutes 
Registration for SP 
Paper # SP2016-67 
Volume (vol) vol.116 
Number (no) no.414 
Page pp.17-22 
#Pages 6 
Date of Issue 2017-01-14 (SP) 

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