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Paper Abstract and Keywords
Presentation 2023-02-28 09:10
Comparison of fundamental frequency controllable fast neural waveform generative models.
Sota Shimizu (Kobe Univ./NICT), Takuma Okamoto (NICT), Ryoichi Takashima, Tetsuya Takiguchi (Kobe Univ.), Tomoki Toda (Nagoya Univ./NICT), Hisashi Kawai (NICT) EA2022-75 SIP2022-119 SP2022-39
Abstract (in Japanese) (See Japanese page) 
(in English) Neural vocoders, which reconstruct speech waveforms from acoustic features with deep neural networks, have significantly improved synthetic speech quality compared to conventional source-filter vocoders. Neural vocoders, like conventional source filter vocoders, are required to be able to flexibly control attributes such as fundamental frequency ($f_{mathrm{o}}$). Harmonic-Net+ and SiFi-GAN have been proposed as models that can synthesize a speech waveform in real time on CPU, while maintaining controllability of $f_{mathrm{o}}$ and high synthetic speech quality. In this study, we conduct experiments to evaluate Harmonic-Net+, MS-Harmonic-Net+ and SiFi-GAN, which are fast neural vocoders with controllability of $f_{mathrm{o}}$ for unseen speaker synthesis.
Keyword (in Japanese) (See Japanese page) 
(in English) speech synthesis / Neural vocoder / fundamental frequency control / real-time inference / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 389, SP2022-39, pp. 1-6, Feb. 2023.
Paper # SP2022-39 
Date of Issue 2023-02-21 (EA, SIP, SP) 
ISSN 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 EA2022-75 SIP2022-119 SP2022-39

Conference Information
Committee SP IPSJ-SLP EA SIP  
Conference Date 2023-02-28 - 2023-03-01 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SP 
Conference Code 2023-02-SP-SLP-EA-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Comparison of fundamental frequency controllable fast neural waveform generative models. 
Sub Title (in English)  
Keyword(1) speech synthesis  
Keyword(2) Neural vocoder  
Keyword(3) fundamental frequency control  
Keyword(4) real-time inference  
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1st Author's Name Sota Shimizu  
1st Author's Affiliation Kobe University/National Institute of Information and Communications Technology (Kobe Univ./NICT)
2nd Author's Name Takuma Okamoto  
2nd Author's Affiliation National Institute of Information and Communications Technology (NICT)
3rd Author's Name Ryoichi Takashima  
3rd Author's Affiliation Kobe University (Kobe Univ.)
4th Author's Name Tetsuya Takiguchi  
4th Author's Affiliation Kobe University (Kobe Univ.)
5th Author's Name Tomoki Toda  
5th Author's Affiliation Nagoya University/National Institute of Information and Communications Technology (Nagoya Univ./NICT)
6th Author's Name Hisashi Kawai  
6th Author's Affiliation National Institute of Information and Communications Technology (NICT)
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Speaker Author-1 
Date Time 2023-02-28 09:10:00 
Presentation Time 20 minutes 
Registration for SP 
Paper # EA2022-75, SIP2022-119, SP2022-39 
Volume (vol) vol.122 
Number (no) no.387(EA), no.388(SIP), no.389(SP) 
Page pp.1-6 
#Pages 6 
Date of Issue 2023-02-21 (EA, SIP, SP) 

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