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Paper Abstract and Keywords
Presentation 2017-01-21 15:10
A Study on the Construction of Articulatory to Acoustic Mapping by Using Deep Neural Network
Fumiaki Taguchi, Tokihiko Kaburagi (Kyushu Univ.) SP2016-73
Abstract (in Japanese) (See Japanese page) 
(in English) This paper presents a method for estimating time series of the acoustic property of the vocal tract expressed by line spectral frequencies from the movement trajectory of the articulatory organs observed with a magnetic sensor (EMA). Statistical methods have been used thus far for the articulatory-to-acoustic mapping because of the difficulty in modeling the relationship between both parameters physically. In this study, articulatory-to-acoustic mapping was constructed by using deep neural network, more specifically a multilayer perceptron, for which effectiveness has been confirmed in various problems. Experimental results showed that the cepstrum error in our estimation method was 3.39 dB when mngu0 dataset was used.
Keyword (in Japanese) (See Japanese page) 
(in English) articulatory movement / vocal tract spectrum / DNN / articulatory-to-acoustic mapping / / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 414, SP2016-73, pp. 53-57, Jan. 2017.
Paper # SP2016-73 
Date of Issue 2017-01-14 (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)
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Conference Information
Committee SP  
Conference Date 2017-01-21 - 2017-01-21 
Place (in Japanese) (See Japanese page) 
Place (in English) The University of Tokyo 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Synthesis, Generation, Prosody, etc. 
Paper Information
Registration To SP 
Conference Code 2017-01-SP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on the Construction of Articulatory to Acoustic Mapping by Using Deep Neural Network 
Sub Title (in English)  
Keyword(1) articulatory movement  
Keyword(2) vocal tract spectrum  
Keyword(3) DNN  
Keyword(4) articulatory-to-acoustic mapping  
1st Author's Name Fumiaki Taguchi  
1st Author's Affiliation Kyushu University (Kyushu Univ.)
2nd Author's Name Tokihiko Kaburagi  
2nd Author's Affiliation Kyushu University (Kyushu Univ.)
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Speaker Author-1 
Date Time 2017-01-21 15:10:00 
Presentation Time 25 minutes 
Registration for SP 
Paper # SP2016-73 
Volume (vol) vol.116 
Number (no) no.414 
Page pp.53-57 
Date of Issue 2017-01-14 (SP) 

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