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Paper Abstract and Keywords
Presentation 2018-08-23 15:10
Investigation of abnormal sound detectionusing occurrence probability of regularsound based on Gaussian Mixture Model
Koji Abe, Moeko Hara, Shouichi Takane, Masayuki Nishiguchi, Kanji Watanabe (Akita Pref. Univ.) EA2018-34
Abstract (in Japanese) (See Japanese page) 
(in English) In most abnormal sound detection systems, abnormal sounds are defined in advance and abnormal sounds are detected by matching with them. We have constructed an abnormal sound detection system which detects mismatched sound which is not suitable for the model of regular sound as abnormal sound. In the proposed system, a regular sound model is represented by a Gaussian mixed model in a space composed of multidimensional acoustic feature vectors. When the occurrence probability of the evaluation sound calculated from the model is small, the evaluation sound is determined to be abnormal sound. Using two groups of sound source imitating daytime and late night, we conducted an abnormal sound detection experiment. As a result, appropriate abnormal sounds were detected according to the sound source group.
Keyword (in Japanese) (See Japanese page) 
(in English) abnormal sound detection / Gaussian Mixture Model / / / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 190, EA2018-34, pp. 37-44, Aug. 2018.
Paper # EA2018-34 
Date of Issue 2018-08-16 (EA) 
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 EA2018-34

Conference Information
Committee EA ASJ-H  
Conference Date 2018-08-23 - 2018-08-24 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku Gakuin Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Engineering/Electro Acoustics, Psychological and Physiological Acoustics, and Related Topics 
Paper Information
Registration To EA 
Conference Code 2018-08-EA-H 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Investigation of abnormal sound detectionusing occurrence probability of regularsound based on Gaussian Mixture Model 
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Keyword(1) abnormal sound detection  
Keyword(2) Gaussian Mixture Model  
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1st Author's Name Koji Abe  
1st Author's Affiliation Akita Prefectural University (Akita Pref. Univ.)
2nd Author's Name Moeko Hara  
2nd Author's Affiliation Akita Prefectural University (Akita Pref. Univ.)
3rd Author's Name Shouichi Takane  
3rd Author's Affiliation Akita Prefectural University (Akita Pref. Univ.)
4th Author's Name Masayuki Nishiguchi  
4th Author's Affiliation Akita Prefectural University (Akita Pref. Univ.)
5th Author's Name Kanji Watanabe  
5th Author's Affiliation Akita Prefectural University (Akita Pref. Univ.)
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Speaker Author-1 
Date Time 2018-08-23 15:10:00 
Presentation Time 25 minutes 
Registration for EA 
Paper # EA2018-34 
Volume (vol) vol.118 
Number (no) no.190 
Page pp.37-44 
#Pages 8 
Date of Issue 2018-08-16 (EA) 

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