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Paper Abstract and Keywords
Presentation 2018-03-20 09:00
[Poster Presentation] Development of NU Voice Conversion System 2018
Patrick Lumban Tobing, Yi-Chiao Wu, Tomoki Hayashi, Kazuhiro Kobayashi (Nagoya Univ.), Tomoki Toda (Nagoya Univ./JST PRESTO) EA2017-138 SIP2017-147 SP2017-121
Abstract (in Japanese) (See Japanese page) 
(in English) This paper presents NU (Nagoya University) voice conversion (VC) system for the HUB task of Voice
Conversion Challenge 2018 (VCC 2018). The design of the NU VC system can basically be separated into
two modules consisting of a speech parameters conversion module and a waveform processing module. In
the speech parameters conversion module, deep learning framework is deployed in estimating spectral parameters of a target speaker given those of a source speaker. Specifically, the deep neural network (DNN) and deep mixture density network (DMDN) are used as the deep model structure. In the waveform processing module, given the estimated spectral parameters and linearly transformed F0 parameters, the converted waveform is generated by using a WaveNet-based vocoder system. To use the WaveNet-based vocoder, there are several generation flows based on analysis-synthesis framework to obtain the speech parameters set, on which a system selection process is performed to select the best one in an utterance-wise manner. The results of VCC 2018 ranked the NU VC system in the 2nd place with an overall of 3.48 mean opinion score (MOS) for speech quality and 83% accuracy for speaker similarity.
Keyword (in Japanese) (See Japanese page) 
(in English) voice conversion / deep learning models / WaveNet vocoder / waveform modeling / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 517, SP2017-121, pp. 203-208, March 2018.
Paper # SP2017-121 
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 EA2017-138 SIP2017-147 SP2017-121

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 Voice Conversion System 2018 
Sub Title (in English)  
Keyword(1) voice conversion  
Keyword(2) deep learning models  
Keyword(3) WaveNet vocoder  
Keyword(4) waveform modeling  
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1st Author's Name Patrick Lumban Tobing  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Yi-Chiao Wu  
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/JST PRESTO (Nagoya Univ./JST PRESTO)
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Speaker Author-1 
Date Time 2018-03-20 09:00:00 
Presentation Time 90 minutes 
Registration for SP 
Paper # EA2017-138, SIP2017-147, SP2017-121 
Volume (vol) vol.117 
Number (no) no.515(EA), no.516(SIP), no.517(SP) 
Page pp.203-208 
#Pages
Date of Issue 2018-03-12 (EA, SIP, SP) 


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