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Paper Abstract and Keywords
Presentation 2018-11-21 13:30
Evaluation of DNN-based Low-Musical-Noise Speech Enhancement Using Kurtosis Matching
Satoshi Mizoguchi, Yuki Saito, Shinnosuke Takamichi, Hiroshi Saruwatari (UTokyo) EA2018-66 EMM2018-66
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes DNN-based speech enhancement with low musical noise by kurtosis matching. Musical noise, artifacts generated by nonlinear signal processing, causes a negative effect on the auditory impression. Quantity of the generated musical noise is significantly correlated with increase in kurtosis from observed signal to enhanced signal. Although soft-mask-based DNN speech enhancement has a high performance on noise reduction thanks to rich power of expression of DNN, it does not consider generation of musical noise. This paper proposes low-musical-noise speech enhancement without degrading noise-reduction-rate and generating significant speech distortion by applying kurtosis matching, which is regularization to prevent kurtosis from increasing, to DNN-based speech enhancement. We give objective evaluation of the enhanced speech signal to demonstrate the efficiency of the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) speech enhancement / musical noise / kurtosis matching / deep learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 312, EA2018-66, pp. 19-24, Nov. 2018.
Paper # EA2018-66 
Date of Issue 2018-11-14 (EA, EMM) 
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 EA2018-66 EMM2018-66

Conference Information
Committee EA ASJ-H EMM IPSJ-MUS  
Conference Date 2018-11-21 - 2018-11-22 
Place (in Japanese) (See Japanese page) 
Place (in English) Hotel Koshuen 
Topics (in Japanese) (See Japanese page) 
Topics (in English) [Beginners Session] Engineering/Electro Acoustics, Psychological and Physiological Acoustics, Music and Computer, Content Processing, Digital Watermarking, and Related Topics 
Paper Information
Registration To EA 
Conference Code 2018-11-EA-H-EMM-MUS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Evaluation of DNN-based Low-Musical-Noise Speech Enhancement Using Kurtosis Matching 
Sub Title (in English)  
Keyword(1) speech enhancement  
Keyword(2) musical noise  
Keyword(3) kurtosis matching  
Keyword(4) deep learning  
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1st Author's Name Satoshi Mizoguchi  
1st Author's Affiliation The University of Tokyo (UTokyo)
2nd Author's Name Yuki Saito  
2nd Author's Affiliation The University of Tokyo (UTokyo)
3rd Author's Name Shinnosuke Takamichi  
3rd Author's Affiliation The University of Tokyo (UTokyo)
4th Author's Name Hiroshi Saruwatari  
4th Author's Affiliation The University of Tokyo (UTokyo)
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Speaker Author-1 
Date Time 2018-11-21 13:30:00 
Presentation Time 150 minutes 
Registration for EA 
Paper # EA2018-66, EMM2018-66 
Volume (vol) vol.118 
Number (no) no.312(EA), no.313(EMM) 
Page pp.19-24 
#Pages 6 
Date of Issue 2018-11-14 (EA, EMM) 

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