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Paper Abstract and Keywords
Presentation 2018-07-26 16:15
Ladder Network Driven from Auditory Computational Model for Multi-talker Speech Separation
Hiroshi Sekiguchi, Yoshiaki Narusue, Hiroyuki Morikawa (Univ. of Tokyo) SP2018-18
Abstract (in Japanese) (See Japanese page) 
(in English) This paper introduces ladder network implementation induced by auditory computational model for multi-talker speech separation. The conventional approach of learning mask ratio of spectrum has been intensively investigated. However, compared with auditory system, it remains limiting in performance in such a way that reconstructed speech shows signal-to distortion ratio (SDR) around 10dB at best. To improve SDR performance, we are inspired by auditory neuroscience, which says speech separation consists of two functions, auditory speech feature extraction and temporal synchronization detection and clustering. The first analyzes speech features and the latter extracts features varying synchronized with the low-frequency-below-5Hz movement of mouth, which are grouped as one speaker, whereas unsynchronized movement grouped as different one. We consider the importance of affinity constraint between these two functions. We derive two different computational models from two functions with this constraint. Then ladder network implements these two computational models with suitable network structures to proper reconstruction path.
Keyword (in Japanese) (See Japanese page) 
(in English) speech separation / temporal coherence / auditory neuroscience / ladder network / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 160, SP2018-18, pp. 9-13, July 2018.
Paper # SP2018-18 
Date of Issue 2018-07-19 (SP) 
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 SP2018-18

Conference Information
Committee SP IPSJ-SLP  
Conference Date 2018-07-26 - 2018-07-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Sago-Royal-Hotel (Hamamatsu) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Speech recognition and understanding, dialog system, etc. 
Paper Information
Registration To SP 
Conference Code 2018-07-SP-SLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Ladder Network Driven from Auditory Computational Model for Multi-talker Speech Separation 
Sub Title (in English)  
Keyword(1) speech separation  
Keyword(2) temporal coherence  
Keyword(3) auditory neuroscience  
Keyword(4) ladder network  
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Keyword(6)  
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1st Author's Name Hiroshi Sekiguchi  
1st Author's Affiliation The University of Tokyo (Univ. of Tokyo)
2nd Author's Name Yoshiaki Narusue  
2nd Author's Affiliation The University of Tokyo (Univ. of Tokyo)
3rd Author's Name Hiroyuki Morikawa  
3rd Author's Affiliation The University of Tokyo (Univ. of Tokyo)
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Speaker Author-1 
Date Time 2018-07-26 16:15:00 
Presentation Time 30 minutes 
Registration for SP 
Paper # SP2018-18 
Volume (vol) vol.118 
Number (no) no.160 
Page pp.9-13 
#Pages 5 
Date of Issue 2018-07-19 (SP) 

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