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Paper Abstract and Keywords
Presentation 2017-03-01 12:40
[Poster Presentation] Prosodic Word Embeddings for DNN-based speech synthesis
Yusuke Ijima, Nobukatsu Hojo, Ryo Masumura, Taichi Asami (NTT) EA2016-109 SIP2016-164 SP2016-104
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposed a novel word embeddings with prosodic information (prosodic word embeddings) for DNN-based speech synthesis. There have been several attempts to use word embeddings for DNN-based speech synthesis. However, their word vectors do not necessarily correspond to prosodic similarity because the training data is a large text corpus. To achieve word embeddings which can take prosodic information into account, we utilize a large speech corpus such as speech corpus for automatic speech recognition. By using the corpus, the proposed technique trains the relationship between words and their prosodic information. We perform objective evaluations to compare the performance of the proposed technique with that of the conventional word embeddings. Objective evaluation results indicate that our proposed word embedding technique can generate F0 more accurately compared to the conventional technique.
Keyword (in Japanese) (See Japanese page) 
(in English) Statistical parametric speech synthesis / DNN-based speech synthesis / word embeddings / / / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 477, SP2016-104, pp. 153-158, March 2017.
Paper # SP2016-104 
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 EA2016-109 SIP2016-164 SP2016-104

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) Prosodic Word Embeddings for DNN-based speech synthesis 
Sub Title (in English)  
Keyword(1) Statistical parametric speech synthesis  
Keyword(2) DNN-based speech synthesis  
Keyword(3) word embeddings  
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1st Author's Name Yusuke Ijima  
1st Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
2nd Author's Name Nobukatsu Hojo  
2nd Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
3rd Author's Name Ryo Masumura  
3rd Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
4th Author's Name Taichi Asami  
4th Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
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Date Time 2017-03-01 12:40:00 
Presentation Time 90 minutes 
Registration for SP 
Paper # EA2016-109, SIP2016-164, SP2016-104 
Volume (vol) vol.116 
Number (no) no.475(EA), no.476(SIP), no.477(SP) 
Page pp.153-158 
#Pages
Date of Issue 2017-02-22 (EA, SIP, SP) 


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