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Paper Abstract and Keywords
Presentation 2014-12-16 11:00
Multimodal Voice Conversion using Weighted Features in Noisy Environments
Kenta Masaka, Ryo Aihara, Tetsuya Takiguchi, Yasuo Ariki (Kobe Univ.) SP2014-116
Abstract (in Japanese) (See Japanese page) 
(in English) Voice conversion is a technique for converting specific information in speech while maintaining the other information, such as linguistic information.
This technique has been applied to various tasks, for example, there are speaker conversion, emotion conversion and speaking assistance, etc.
The GMM-based method is conventional VC method and widely used.
In noisy environments, the GMM-based method cannot convert the speech well, because this method cannot model the noisy signal well.
Therefore, we have been researched about a noise-robust VC method using Non Negative Matrix Factorization (NMF).
In this paper, we propose a multimodal VC method that improves the noise robustness of our previous exemplar-based VC method.
Furthermore, we introduce the combination weight between audio and visual features and formulate a new cost function in order to estimate the audio-visual exemplars.
By using the joint audio-visual features as source features, the VC performance is improved compared to a previous audio-input exemplar-based VC method.
The effectiveness of this method was confirmed by comparing it with that of the
conventional audio input NMF-based method and the conventional GMM-based method.
Keyword (in Japanese) (See Japanese page) 
(in English) voice conversion / multimodal / image features / non-negative matrix factorization / noisy environments / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 365, SP2014-116, pp. 87-92, Dec. 2014.
Paper # SP2014-116 
Date of Issue 2014-12-08 (SP) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 SP2014-116

Conference Information
Conference Date 2014-12-15 - 2014-12-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Tokyo Institute of Technology (Suzukakedai Campus) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) The 6th Symposium on Collective Knowlege 
Paper Information
Registration To SP 
Conference Code 2014-12-NLC-NL-SP-SLP-SLUD 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Multimodal Voice Conversion using Weighted Features in Noisy Environments 
Sub Title (in English)  
Keyword(1) voice conversion  
Keyword(2) multimodal  
Keyword(3) image features  
Keyword(4) non-negative matrix factorization  
Keyword(5) noisy environments  
1st Author's Name Kenta Masaka  
1st Author's Affiliation Kobe University (Kobe Univ.)
2nd Author's Name Ryo Aihara  
2nd Author's Affiliation Kobe University (Kobe Univ.)
3rd Author's Name Tetsuya Takiguchi  
3rd Author's Affiliation Kobe University (Kobe Univ.)
4th Author's Name Yasuo Ariki  
4th Author's Affiliation Kobe University (Kobe Univ.)
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Date Time 2014-12-16 11:00:00 
Presentation Time 90 
Registration for SP 
Paper # IEICE-SP2014-116 
Volume (vol) IEICE-114 
Number (no) no.365 
Page pp.87-92 
#Pages IEICE-6 
Date of Issue IEICE-SP-2014-12-08 

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