Paper Abstract and Keywords |
Presentation |
2018-07-24 11:20
Performance Enhancement of a Wind noise reduction method using DNN Toya Kitagawa, Kazuhiro Kondo (Yamagata Univ.), Yosuke Kobayashi (Muroran Institute of Technology) EA2018-3 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In a speech navigation system using bicycle Audio Augmented Reality, blocking of the environmental sound by wearing the ear with a presentation device such as an earphone becomes a problem. Therefore, a microphone and a earphone are integrated in to a hear-through earphone which transparently presents ambient environmental sound. In using this, there is a problem that not only environmental sound but also wind noise is acquired, so it is difficult to hear navigation sounds and environmental sounds. Accordingly, in previous research, various wind noise reduction methods under conditions actually used on real time in the bicycle were systematically evaluated and compared. We have concluded that the Wiener (iteration) filter is most effective for wind noise reduction. However, the Wiener (iteration) filter has a problem that not only wind noise but environmental sound is overly attenuated. Therefore, in the previous study, we studied wind noise reduction by Deep Learning (DNN) as a new wind noise reduction method. In supervised learning, the input is wind noise mixed with a car horn, and the output is only the car horn. As a result, the wind noise part could be completely eliminated. However, the timbre of horn changed, and when there is horn, wind noise was reproduced at the same time. In this time, in order to practically train the DNN with a large amount of data, when adding horn to wind noise, wind noise was shifted by 0.1 second at a time to simulate various wind noises. As a result, we succeeded in preventing the change of the timbre of the horn and the reproduction of the wind noise while maintaining the wind noise elimination performance. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Audio Augmented Reality / Wind noise / Environmental sound / DNN (Deep Neural Network) / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 149, EA2018-3, pp. 13-18, July 2018. |
Paper # |
EA2018-3 |
Date of Issue |
2018-07-17 (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) |
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EA2018-3 |
Conference Information |
Committee |
EA ASJ-H ASJ-AA |
Conference Date |
2018-07-24 - 2018-07-25 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Hokkaido Univ. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Engineering/Electro Acoustics, Psychological and Physiological Acoustics, Architectural Acoustics, Education in Acoustics, and Related Topics |
Paper Information |
Registration To |
EA |
Conference Code |
2018-07-EA-H-AA |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Performance Enhancement of a Wind noise reduction method using DNN |
Sub Title (in English) |
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Keyword(1) |
Audio Augmented Reality |
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Wind noise |
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Environmental sound |
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DNN (Deep Neural Network) |
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1st Author's Name |
Toya Kitagawa |
1st Author's Affiliation |
Yamagata Universty (Yamagata Univ.) |
2nd Author's Name |
Kazuhiro Kondo |
2nd Author's Affiliation |
Yamagata Universty (Yamagata Univ.) |
3rd Author's Name |
Yosuke Kobayashi |
3rd Author's Affiliation |
Muroran Institute of Technology (Muroran Institute of Technology) |
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Speaker |
Author-1 |
Date Time |
2018-07-24 11:20:00 |
Presentation Time |
25 minutes |
Registration for |
EA |
Paper # |
EA2018-3 |
Volume (vol) |
vol.118 |
Number (no) |
no.149 |
Page |
pp.13-18 |
#Pages |
6 |
Date of Issue |
2018-07-17 (EA) |
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