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Paper Abstract and Keywords
Presentation 2017-03-01 10:25
Noisy speech reconstruction based on deep neural network with optical microphone
Tomoyuki Mizuno, Takahiro Fukumori, Masato Nakayama, Takanobu Nishiura (Ritsumeikan Univ.) EA2016-84 SIP2016-139 SP2016-79
Abstract (in Japanese) (See Japanese page) 
(in English) Measuring distant-talking speech with high accuracy is important for detecting criminal activity. Various microphones such as the parabolic and shotgun microphones have been developed for measuring it. However, most of them have difficulty in extracting distant-talking speech at a target position if they are surrounded by noisy sound sources. Therefore, this study focuses on an optical microphone which uses a laser light for extracting the distant-talking speech. The optical microphone is realized by a laser doppler vibrometer. The sound quality of the optical microphone is especially degraded at higher frequencies because it utilizes an external diaphragm consisting of various materials as the vibrating papery object. In this study, we therefore propose a reconstruction method with a deep neural network that uses a complex spectrum as an input signal. Finally, we confirmed the effectiveness of the proposed system through an evaluation experiment.
Keyword (in Japanese) (See Japanese page) 
(in English) Optical microphone / Speech reconstruction / Deep neural network / Laser doppler vibrometer / Complex spectrum / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 475, EA2016-84, pp. 13-18, March 2017.
Paper # EA2016-84 
Date of Issue 2017-02-22 (EA, SIP, SP) 
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 EA2016-84 SIP2016-139 SP2016-79

Conference Information
Committee SP SIP EA  
Conference Date 2017-03-01 - 2017-03-02 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Industry Support Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Speech, Engineering/Electro Acoustics, Signal Processing, and Related Topics 
Paper Information
Registration To EA 
Conference Code 2017-03-SP-SIP-EA 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Noisy speech reconstruction based on deep neural network with optical microphone 
Sub Title (in English)  
Keyword(1) Optical microphone  
Keyword(2) Speech reconstruction  
Keyword(3) Deep neural network  
Keyword(4) Laser doppler vibrometer  
Keyword(5) Complex spectrum  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Tomoyuki Mizuno  
1st Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
2nd Author's Name Takahiro Fukumori  
2nd Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
3rd Author's Name Masato Nakayama  
3rd Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
4th Author's Name Takanobu Nishiura  
4th Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
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Speaker Author-1 
Date Time 2017-03-01 10:25:00 
Presentation Time 25 minutes 
Registration for EA 
Paper # EA2016-84, SIP2016-139, SP2016-79 
Volume (vol) vol.116 
Number (no) no.475(EA), no.476(SIP), no.477(SP) 
Page pp.13-18 
#Pages 6 
Date of Issue 2017-02-22 (EA, SIP, SP) 

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