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Paper Abstract and Keywords
Presentation 2015-10-15 16:45
A study on quick model training in HMM-based speech synthesis
Shuhei Yamada, Takashi Nose, Akinori Ito (Tohoku Univ.) SP2015-64
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose an alternative model training technique using speaker-independent monophone models and decision trees to speed up the model training process of HMM-based speech synthesis. Recently, speech synthesis is used in various situations, and the demand of making speaker models by users themselves and synthesizing voices which reflects users' characteristic will increase.
The HMM-based approach has an advantage of reflecting speaking styles and individualities to synthetic speech; however, it is not easy to train a reliable speaker-dependent model in a short time using prepared target speaker's speech because the model training process is computationally expensive compared with the synthesis process for it needs several time-consuming calculation such as decision tree construction. In the proposed technique, we use speaker-independent monophone models and decision trees instead of the conventional speaker-dependent ones. We also speed up the training process by skipping the parameter update based on maximum likelihood estimation. The objective and subjective experimental results show that the proposed training technique can synthesize speech having similar naturalness to the conventional training with less than 40% training time of the conventional one.
Keyword (in Japanese) (See Japanese page) 
(in English) HMM-based speech synthesi / model training / computation time reduction / speaker-independent models / context clustering / / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 253, SP2015-64, pp. 27-32, Oct. 2015.
Paper # SP2015-64 
Date of Issue 2015-10-08 (SP) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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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Conference Information
Committee SP  
Conference Date 2015-10-15 - 2015-10-16 
Place (in Japanese) (See Japanese page) 
Place (in English) Kobe Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Speech interface, Synthesis, Dialogue, Application system, etc. 
Paper Information
Registration To SP 
Conference Code 2015-10-SP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A study on quick model training in HMM-based speech synthesis 
Sub Title (in English)  
Keyword(1) HMM-based speech synthesi  
Keyword(2) model training  
Keyword(3) computation time reduction  
Keyword(4) speaker-independent models  
Keyword(5) context clustering  
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1st Author's Name Shuhei Yamada  
1st Author's Affiliation Tohoku University (Tohoku Univ.)
2nd Author's Name Takashi Nose  
2nd Author's Affiliation Tohoku University (Tohoku Univ.)
3rd Author's Name Akinori Ito  
3rd Author's Affiliation Tohoku University (Tohoku Univ.)
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Speaker Author-1 
Date Time 2015-10-15 16:45:00 
Presentation Time 25 minutes 
Registration for SP 
Paper # SP2015-64 
Volume (vol) vol.115 
Number (no) no.253 
Page pp.27-32 
#Pages
Date of Issue 2015-10-08 (SP) 


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