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Paper Abstract and Keywords
Presentation 2017-03-01 09:20
Speech waveform synthesis based on WaveNet considering speech generation process
Akira Tamamori, Tomoki Hayashi, Tomoki Toda, Kazuya Takeda (Nagoya Univ.) EA2016-82 SIP2016-137 SP2016-77
Abstract (in Japanese) (See Japanese page) 
(in English) Our aim is to realize a new vocoder, which can resolve various constraints imposed on source-filter model and deal with speech waveform directly. In this study, we propose a method of synthesizing speech waveforms with WaveNet, which was a recently proposed neural network for generating audio signal waveforms, by using existing vocoder parameters as input auxiliary features. It is expected that these parameters are effective for auxiliary feature of waveform generation, because they are based on source-filter model. In the experiment, parameters of mel-cepstrum vocoder were selected as target, and quality of synthesized speech was objectively evaluated by SNR (Signal-to-Noise Ratio) and SDR (Signal-to-Distortion Ratio). From the results, it was confirmed that the sound quality was significantly improved for SNR and proposed method was effective.
Keyword (in Japanese) (See Japanese page) 
(in English) WaveNet / convolutional neural network / source-filter model / mel-cepstrum / fundamental frequency. / vocoder / deep leaning /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 477, SP2016-77, pp. 1-6, March 2017.
Paper # SP2016-77 
Date of Issue 2017-02-22 (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 EA2016-82 SIP2016-137 SP2016-77

Conference Information
Committee SP SIP EA  
Conference Date 2017-03-01 - 2017-03-02 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Industry Support Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Speech, Engineering/Electro Acoustics, Signal Processing, and Related Topics 
Paper Information
Registration To SP 
Conference Code 2017-03-SP-SIP-EA 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Speech waveform synthesis based on WaveNet considering speech generation process 
Sub Title (in English)  
Keyword(1) WaveNet  
Keyword(2) convolutional neural network  
Keyword(3) source-filter model  
Keyword(4) mel-cepstrum  
Keyword(5) fundamental frequency.  
Keyword(6) vocoder  
Keyword(7) deep leaning  
Keyword(8)  
1st Author's Name Akira Tamamori  
1st Author's Affiliation Nagoya University/JST (Nagoya Univ.)
2nd Author's Name Tomoki Hayashi  
2nd Author's Affiliation Nagoya University (Nagoya Univ.)
3rd Author's Name Tomoki Toda  
3rd Author's Affiliation Nagoya University (Nagoya Univ.)
4th Author's Name Kazuya Takeda  
4th Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker Author-1 
Date Time 2017-03-01 09:20:00 
Presentation Time 25 minutes 
Registration for SP 
Paper # EA2016-82, SIP2016-137, SP2016-77 
Volume (vol) vol.116 
Number (no) no.475(EA), no.476(SIP), no.477(SP) 
Page pp.1-6 
#Pages 6 
Date of Issue 2017-02-22 (EA, SIP, SP) 

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