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Paper Abstract and Keywords
Presentation 2020-03-03 09:00
Cross-Lingual Voice Conversion using Cyclic Variational Auto-encoder
Hikaru Nakatani, Patrick Lumban Tobing, Kazuya Takeda, Tomoki Toda (Nagoya Univ.) EA2019-139 SIP2019-141 SP2019-88
Abstract (in Japanese) (See Japanese page) 
(in English) In this report, we present a novel cross-lingual voice conversion (VC) method based on cyclic variational auto-encoder (CycleVAE). Cross-lingual VC is a technique to perform VC between source and target speakers who speak different languages. To use a VC method based on parallel learning, it is necessary to prepare training data consisting of accented speeches forcibly uttered by the source or the target speaker based on their mother tongue’s pronunciation systems. On the other hand, to use a VC method based on non-parallel learning, both the source and the target speakers' natural speech data in different languages are available. In that case, however, it is required to handle not only a time-alignment issue but also a language mismatch issue between the source and target speakers. To address these issues, we apply CycleVAE to cross-lingual VC as a more sophisticated non-parallel VC method than a traditional variational auto-encoder (VAE)-based method. From the experimental results of the cross-lingual VC from a native English speaker to a native Japanese speaker, it has been verified that the proposed method based on CycleVAE achieves higher naturalness than a parallel VC method using accented speech data.
Keyword (in Japanese) (See Japanese page) 
(in English) voice conversion / cross-lingual / non-parallel / cyclic variational auto-encoder / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 441, SP2019-88, pp. 219-224, March 2020.
Paper # SP2019-88 
Date of Issue 2020-02-24 (EA, SIP, SP) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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 EA2019-139 SIP2019-141 SP2019-88

Conference Information
Committee SP EA SIP  
Conference Date 2020-03-02 - 2020-03-03 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Industry Support Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SP 
Conference Code 2020-03-SP-EA-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Cross-Lingual Voice Conversion using Cyclic Variational Auto-encoder 
Sub Title (in English)  
Keyword(1) voice conversion  
Keyword(2) cross-lingual  
Keyword(3) non-parallel  
Keyword(4) cyclic variational auto-encoder  
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1st Author's Name Hikaru Nakatani  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Patrick Lumban Tobing  
2nd Author's Affiliation Nagoya University (Nagoya Univ.)
3rd Author's Name Kazuya Takeda  
3rd Author's Affiliation Nagoya University (Nagoya Univ.)
4th Author's Name Tomoki Toda  
4th Author's Affiliation Nagoya University (Nagoya Univ.)
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Date Time 2020-03-03 09:00:00 
Presentation Time 90 minutes 
Registration for SP 
Paper # EA2019-139, SIP2019-141, SP2019-88 
Volume (vol) vol.119 
Number (no) no.439(EA), no.440(SIP), no.441(SP) 
Page pp.219-224 
#Pages
Date of Issue 2020-02-24 (EA, SIP, SP) 


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