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 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) |
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EMM2018-86 |
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) |
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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 |
6 |
Date of Issue |
2019-01-03 (EMM) |
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