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) |
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Statistical parametric speech synthesis |
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DNN-based speech synthesis |
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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 |
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Nippon Telegraph and Telephone Corporation (NTT) |
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Speaker |
Author-1 |
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 |
6 |
Date of Issue |
2017-02-22 (EA, SIP, SP) |
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