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 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) |
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) |
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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 |
6 |
Date of Issue |
2018-03-12 (EA, SIP, SP) |
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