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Paper Abstract and Keywords
Presentation 2013-12-19 16:00
Improvement of AF-based Voice Conversion for Arbitrary Speakers
Narpendyah Wisjnu Ariwardhani (TUT), Yurie Iribe (Aichi Prefectureal Univ.), Kouichi Katsurada (TUT), Tsuneo Nitta (Waseda Univ.) SP2013-85
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we use artificial neural networks (ANNs) for articulatory feature (AF) based voice conversion. ANNs are applied to map AF to vocal tract parameter (VTP) and to convert the source speaker?s voice to the target speaker?s voice. The proposed system is not only text independent voice conversion, but can also be used for an arbitrary source speaker. This means that our approach requires no source speaker data to build the voice conversion model and hence source speaker data is only required during testing phase. The results of voice conversion were evaluated using subjective and objective measures to compare the performance of our proposed ANN-based voice conversion (VC) with the state-of-the-art Gaussian mixture model (GMM)-based VC. The experimental results show that the converted voice is intelligible and has speaker individuality of the target speaker. Furthermore, preliminary experiments are also conducted to investigate AF flexibility on cross-lingual voice conversion.
Keyword (in Japanese) (See Japanese page) 
(in English) voice conversion / neural network / articulatory feature / arbitrary speaker / cross-lingual / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 366, SP2013-85, pp. 65-70, Dec. 2013.
Paper # SP2013-85 
Date of Issue 2013-12-12 (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 IPSJ-SLP  
Conference Date 2013-12-19 - 2013-12-20 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) 15th Symposium on Spoken Language 
Paper Information
Registration To SP 
Conference Code 2013-12-SP-SLP 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Improvement of AF-based Voice Conversion for Arbitrary Speakers 
Sub Title (in English)  
Keyword(1) voice conversion  
Keyword(2) neural network  
Keyword(3) articulatory feature  
Keyword(4) arbitrary speaker  
Keyword(5) cross-lingual  
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1st Author's Name Narpendyah Wisjnu Ariwardhani  
1st Author's Affiliation Toyohashi University of Technology (TUT)
2nd Author's Name Yurie Iribe  
2nd Author's Affiliation Aichi Prefectural University (Aichi Prefectureal Univ.)
3rd Author's Name Kouichi Katsurada  
3rd Author's Affiliation Toyohashi University of Technology (TUT)
4th Author's Name Tsuneo Nitta  
4th Author's Affiliation Waseda University (Waseda Univ.)
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Speaker Author-1 
Date Time 2013-12-19 16:00:00 
Presentation Time 25 minutes 
Registration for SP 
Paper # SP2013-85 
Volume (vol) vol.113 
Number (no) no.366 
Page pp.65-70 
#Pages
Date of Issue 2013-12-12 (SP) 


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