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Paper Abstract and Keywords
Presentation 2020-12-01 10:50
A study of anomalous sound detection using sound activity detection
Yasuhiro Kanishima, Takashi Sudo (Toshiba) SIS2020-29
Abstract (in Japanese) (See Japanese page) 
(in English) In anomalous sound detection that determines the operation of the device or the quality of the product based on the sound signal generated from the device or product on the mass production line, for the purpose of improving the accuracy and reducing the amount of processing of anomalous sound detection, We propose a segmentation that detects the section in which the device operates from the sound signal using trigger detection and template matching detection. Using the data of the mass production line inspection sound of the rotating body product as a motif, the accuracy of abnormal sound detection by the autoencoder was evaluated for the data segmented by the conventional method and the proposed method. As a result, the AUC for the conventional method was 0.642 and the AUC for the proposed method was 0.997. We confirmed the effect of the accuracy improvement by the proposed method. In addition, intermittent processing for anomalous sound detection is possible, and the effect of reducing the processing amount can be expected.
Keyword (in Japanese) (See Japanese page) 
(in English) Anomalous Sound / Anomaly Detection / Neural Network / Deep Learning / Activity Detection / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 269, SIS2020-29, pp. 12-17, Dec. 2020.
Paper # SIS2020-29 
Date of Issue 2020-11-24 (SIS) 
ISSN 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 SIS2020-29

Conference Information
Committee SIS  
Conference Date 2020-12-01 - 2020-12-01 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Smart Personal Systems, etc. 
Paper Information
Registration To SIS 
Conference Code 2020-12-SIS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A study of anomalous sound detection using sound activity detection 
Sub Title (in English)  
Keyword(1) Anomalous Sound  
Keyword(2) Anomaly Detection  
Keyword(3) Neural Network  
Keyword(4) Deep Learning  
Keyword(5) Activity Detection  
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1st Author's Name Yasuhiro Kanishima  
1st Author's Affiliation Toshiba Corporation (Toshiba)
2nd Author's Name Takashi Sudo  
2nd Author's Affiliation Toshiba Corporation (Toshiba)
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Speaker Author-1 
Date Time 2020-12-01 10:50:00 
Presentation Time 25 minutes 
Registration for SIS 
Paper # SIS2020-29 
Volume (vol) vol.120 
Number (no) no.269 
Page pp.12-17 
#Pages 6 
Date of Issue 2020-11-24 (SIS) 

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