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Paper Abstract and Keywords
Presentation 2018-10-28 12:10
Neural Network based articulation feature analysis system and its application to speech of cleft palate children
Akihiro Eto, Hiroki Arakawa, Masahiro Tezuka, Norihumi Nakamura, Tadashi Sakata, Yuichi Ueda (Kumamoto Univ.) SP2018-47 WIT2018-35
Abstract (in Japanese) (See Japanese page) 
(in English) Speech therapists or dentists evaluate the presence or absence of dysarthria by his/her auditory.
However, its diagnosis is not objective since those evaluations are influenced by listener's auditory experiences.
Therefore, we analyzed abnormal articulation features using a neural network(NN) to diagnose dysarthria objectively.
We applied the NN to healthy and cleft palate voices of commercially speech data in order to capture the articulation features of cleft palate.
Then, we consider practicality of the NN by applying the NN to recorded sound in the same way.
In the end, we applied non-metric multi dimensional scaling to the NN results.
As a result, possibility of visualizing presence or absence of dysarthria is confirmed.
Keyword (in Japanese) (See Japanese page) 
(in English) Cleft palate / Dysarthria / Neural Network / Non-metric Multi Dimentional Scaling / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 270, WIT2018-35, pp. 79-84, Oct. 2018.
Paper # WIT2018-35 
Date of Issue 2018-10-20 (SP, WIT) 
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 WIT SP  
Conference Date 2018-10-27 - 2018-10-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyushu Institute of Technology(Kitakyushu) 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To WIT 
Conference Code 2018-10-WIT-SP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Neural Network based articulation feature analysis system and its application to speech of cleft palate children 
Sub Title (in English)  
Keyword(1) Cleft palate  
Keyword(2) Dysarthria  
Keyword(3) Neural Network  
Keyword(4) Non-metric Multi Dimentional Scaling  
1st Author's Name Akihiro Eto  
1st Author's Affiliation Kumamoto University (Kumamoto Univ.)
2nd Author's Name Hiroki Arakawa  
2nd Author's Affiliation Kumamoto University (Kumamoto Univ.)
3rd Author's Name Masahiro Tezuka  
3rd Author's Affiliation Kumamoto University (Kumamoto Univ.)
4th Author's Name Norihumi Nakamura  
4th Author's Affiliation Kumamoto University (Kumamoto Univ.)
5th Author's Name Tadashi Sakata  
5th Author's Affiliation Kumamoto University (Kumamoto Univ.)
6th Author's Name Yuichi Ueda  
6th Author's Affiliation Kumamoto University (Kumamoto Univ.)
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Date Time 2018-10-28 12:10:00 
Presentation Time 25 
Registration for WIT 
Paper # IEICE-SP2018-47,IEICE-WIT2018-35 
Volume (vol) IEICE-118 
Number (no) no.269(SP), no.270(WIT) 
Page pp.79-84 
#Pages IEICE-6 
Date of Issue IEICE-SP-2018-10-20,IEICE-WIT-2018-10-20 

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