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Paper Abstract and Keywords
Presentation 2019-01-11 09:55
Study on Digital Audio Watermarking Method Based on Singular Spectrum Analysis with Automatic Parameter Estimation Using a Convolutional Neural Network
Kasorn Galajit (JAIST), Jessada Karnjana (NECTEC), Pakinee Aimmanee (SIIT), Masashi Unoki (JAIST) EMM2018-86
Abstract (in Japanese) (See Japanese page) 
(in English) An audio watermarking method based on the singular-spectrum analysis (SSA) with a convolutional neural network (CNN) for parameter estimation is studied. A watermark is embedded by modifying a part of a singular spectrum of an original signal. The modification part must be appropriately selected to balance the robustness and sound quality. In our previous work, a differential evolution (DE) algorithm could effectively select the proper part. However, it is time-consuming. In this study, we replaced DE with CNN-based parameter estimation. The experimental results showed that the computational time is significantly reduced by 96,923 times. The sound quality and the robustness were well balanced. Moreover, the scheme was a blind method.
Keyword (in Japanese) (See Japanese page) 
(in English) automatic parameter estimation / differential evolution / singular spectrum analysis / convolutional neural networks / audio watermarking / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 382, EMM2018-86, pp. 25-30, Jan. 2019.
Paper # EMM2018-86 
Date of Issue 2019-01-03 (EMM) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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)
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Conference Information
Committee EMM  
Conference Date 2019-01-10 - 2019-01-11 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Sense of Presence, Universal Media, Digital Entertainment, etc. 
Paper Information
Registration To EMM 
Conference Code 2019-01-EMM 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Study on Digital Audio Watermarking Method Based on Singular Spectrum Analysis with Automatic Parameter Estimation Using a Convolutional Neural Network 
Sub Title (in English)  
Keyword(1) automatic parameter estimation  
Keyword(2) differential evolution  
Keyword(3) singular spectrum analysis  
Keyword(4) convolutional neural networks  
Keyword(5) audio watermarking  
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1st Author's Name Kasorn Galajit  
1st Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
2nd Author's Name Jessada Karnjana  
2nd Author's Affiliation NECTEC, National Science and Technology Development Agency (NECTEC)
3rd Author's Name Pakinee Aimmanee  
3rd Author's Affiliation Sirindhorn International Institute of Technology, Thammasat University (SIIT)
4th Author's Name Masashi Unoki  
4th Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
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Speaker Author-1 
Date Time 2019-01-11 09:55:00 
Presentation Time 25 minutes 
Registration for EMM 
Paper # EMM2018-86 
Volume (vol) vol.118 
Number (no) no.382 
Page pp.25-30 
#Pages
Date of Issue 2019-01-03 (EMM) 


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