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Paper Abstract and Keywords
Presentation 2016-10-14 14:30
A compression method for multi-channel signal based on the principal component analysis
Hironori Sato, Arif Herusetyo Wicaksono, Shuichi Sakamoto, Cesar Daniel Salvador, Jorge Trevino, Yoiti Suzuki (Tohoku University) EA2016-32
Abstract (in Japanese) (See Japanese page) 
(in English) Network usage costs are a serious obstacle to the transmission of multi-channel microphone arrays recordings when communicating accurate 3D sound. This makes it important to develop efficient compression methods for microphone array signals. Inter-channel correlations are high if average microphone distances are shorter than the wavelengths present in the source, resulting in large redundancies in the recorded data. Principal component analysis (PCA) was previously applied in the time domain to remove such redundancies. In this report, the technique is now applied in the frequency domain by using the discrete cosine transform. Numerical experiments show that the bitrate of the compressed data can be around one third that of the original, uncompressed recordings while retaining high spatial resolution better than conventional audio compression algorithms.
Keyword (in Japanese) (See Japanese page) 
(in English) multi-channel signal compression / principal component analysis / head-related transfer function / eigenvalue decomposition / modified discrete cosine transform / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 246, EA2016-32, pp. 7-11, Oct. 2016.
Paper # EA2016-32 
Date of Issue 2016-10-07 (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 EA2016-32

Conference Information
Committee EA ASJ-H IPSJ-MUS  
Conference Date 2016-10-14 - 2016-10-15 
Place (in Japanese) (See Japanese page) 
Place (in English) Noto Omakidai (Nanao) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Engineering/Electro Acoustics, Psychological and Physiological Acoustics, Music Information Processing, and Related Topics 
Paper Information
Registration To EA 
Conference Code 2016-10-EA-H-MUS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A compression method for multi-channel signal based on the principal component analysis 
Sub Title (in English)  
Keyword(1) multi-channel signal compression  
Keyword(2) principal component analysis  
Keyword(3) head-related transfer function  
Keyword(4) eigenvalue decomposition  
Keyword(5) modified discrete cosine transform  
Keyword(6)  
Keyword(7)  
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1st Author's Name Hironori Sato  
1st Author's Affiliation Tohoku Uniersity (Tohoku University)
2nd Author's Name Arif Herusetyo Wicaksono  
2nd Author's Affiliation Tohoku Uniersity (Tohoku University)
3rd Author's Name Shuichi Sakamoto  
3rd Author's Affiliation Tohoku Uniersity (Tohoku University)
4th Author's Name Cesar Daniel Salvador  
4th Author's Affiliation Tohoku Uniersity (Tohoku University)
5th Author's Name Jorge Trevino  
5th Author's Affiliation Tohoku Uniersity (Tohoku University)
6th Author's Name Yoiti Suzuki  
6th Author's Affiliation Tohoku Uniersity (Tohoku University)
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Speaker Author-1 
Date Time 2016-10-14 14:30:00 
Presentation Time 150 minutes 
Registration for EA 
Paper # EA2016-32 
Volume (vol) vol.116 
Number (no) no.246 
Page pp.7-11 
#Pages 5 
Date of Issue 2016-10-07 (EA) 

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