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 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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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) |
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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) |
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Keyword(1) |
non-parallel voice conversion |
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mixture density neural network |
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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 |
6 |
Date of Issue |
2018-03-12 (EA, SIP, SP) |
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