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Paper Abstract and Keywords
Presentation 2018-03-20 14:45
Development of NU non-parallel Voice Conversion System 2018
Yi-Chiao Wu, Patrick Lumban Tobing, Tomoki Hayashi, Kazuhiro Kobayashi, Tomoki Toda (Nagoya Univ.) EA2017-172 SIP2017-181 SP2017-155
Abstract (in Japanese) (See Japanese page) 
(in English) This paper introduces the NU non-parallel voice conversion (VC) system developed at Nagoya University for SPOKE task of Voice Conversion Challenge 2018 (VCC2018). The goal of the SPOKE task is to develop VC systems without the requirement of parallel training data. In the previous version of the system, we developed a deep neural network (DNN) based cascade VC system to convert the source voice into the target voice via the TTS voice as the reference. However, the two stages conversion caused performance degradation. As a result, in this paper, we propose a compensation AutoEncoder technique to compensate the mismatch between the output of first stage conversion and the input of the second stage conversion. In addition, we also investigate the use of deep mixture density network (DMDN) to avoid the DNN-based limitations of the lack of ability to predict variance and the unimodal nature. The objective evaluation results shows the effectiveness of DMDN and the potential improvement of compensation AutoEncoder.
Keyword (in Japanese) (See Japanese page) 
(in English) non-parallel voice conversion / mixture density neural network / cascade system, compensation AutoEncoder / / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 517, SP2017-155, pp. 385-390, March 2018.
Paper # SP2017-155 
Date of Issue 2018-03-12 (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 EA2017-172 SIP2017-181 SP2017-155

Conference Information
Committee SIP EA SP MI  
Conference Date 2018-03-19 - 2018-03-20 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) Speech, Engineering/Electro Acoustics, Signal Processing, and Related Topics [SIP, EA, SP]/ Medical Image Engineering, Analysis, Recognition, etc. [MI] 
Paper Information
Registration To SP 
Conference Code 2018-03-SIP-EA-SP-MI 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Development of NU non-parallel Voice Conversion System 2018 
Sub Title (in English)  
Keyword(1) non-parallel voice conversion  
Keyword(2) mixture density neural network  
Keyword(3) cascade system, compensation AutoEncoder  
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1st Author's Name Yi-Chiao Wu  
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 Tomoki Hayashi  
3rd Author's Affiliation Nagoya University (Nagoya Univ.)
4th Author's Name Kazuhiro Kobayashi  
4th Author's Affiliation Nagoya University (Nagoya Univ.)
5th Author's Name Tomoki Toda  
5th Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker Author-1 
Date Time 2018-03-20 14:45:00 
Presentation Time 25 minutes 
Registration for SP 
Paper # EA2017-172, SIP2017-181, SP2017-155 
Volume (vol) vol.117 
Number (no) no.515(EA), no.516(SIP), no.517(SP) 
Page pp.385-390 
#Pages
Date of Issue 2018-03-12 (EA, SIP, SP) 


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