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Paper Abstract and Keywords
Presentation 2022-03-02 10:45
Evaluation of sentence-level generation in Japanese dialect speech synthesis using accent latent variables
Kazuya Yufune, Tomoki Koriyama, Shinnosuke Takamichi, Hiroshi Saruwatari (UTokyo) EA2021-79 SIP2021-106 SP2021-64
Abstract (in Japanese) (See Japanese page) 
(in English) Japanese dialect speech synthesis is useful for personalized speech synthesis systems. However, inability to prepare accent labels is an obstacle to improving the naturalness of the synthesized dialectal speeches.
In the past, we proposed an accent-label-free method to model the pitch accent of Japanese dialects as mora-level accent latent variables (ALVs) using vector quantized variational autoencoder (VQ-VAE), and we evaluated its performance for phrase-level utterances.
In this paper, we apply the same method with some modifications to sentence-level dialectal utterances and evaluate it.
The experimental evaluation showed that the ALVs can be used to model the pitch accent even of sentence-level utterances, that the proposed method can synthesize more natural pitch accents from text than the conventional one when the text analysis is accurate, and that the proposed method improves the controllability of synthesized pitch accents.
Keyword (in Japanese) (See Japanese page) 
(in English) Dialect speech synthesis / accent latent variable / VQ-VAE / pitch accent / latent variable / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 385, SP2021-64, pp. 96-101, March 2022.
Paper # SP2021-64 
Date of Issue 2022-02-22 (EA, SIP, SP) 
ISSN Online edition: ISSN 2432-6380
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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 EA2021-79 SIP2021-106 SP2021-64

Conference Information
Committee EA SIP SP IPSJ-SLP  
Conference Date 2022-03-01 - 2022-03-02 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To SP 
Conference Code 2022-03-EA-SIP-SP-SLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Evaluation of sentence-level generation in Japanese dialect speech synthesis using accent latent variables 
Sub Title (in English)  
Keyword(1) Dialect speech synthesis  
Keyword(2) accent latent variable  
Keyword(3) VQ-VAE  
Keyword(4) pitch accent  
Keyword(5) latent variable  
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1st Author's Name Kazuya Yufune  
1st Author's Affiliation the University of Tokyo (UTokyo)
2nd Author's Name Tomoki Koriyama  
2nd Author's Affiliation the University of Tokyo (UTokyo)
3rd Author's Name Shinnosuke Takamichi  
3rd Author's Affiliation the University of Tokyo (UTokyo)
4th Author's Name Hiroshi Saruwatari  
4th Author's Affiliation the University of Tokyo (UTokyo)
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Speaker Author-1 
Date Time 2022-03-02 10:45:00 
Presentation Time 25 minutes 
Registration for SP 
Paper # EA2021-79, SIP2021-106, SP2021-64 
Volume (vol) vol.121 
Number (no) no.383(EA), no.384(SIP), no.385(SP) 
Page pp.96-101 
#Pages
Date of Issue 2022-02-22 (EA, SIP, SP) 


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