Paper Abstract and Keywords |
Presentation |
2022-06-17 15:00
Neural beamformer with automatic detection of notable sounds for acoustic scene classification Sota Ichikawa, Takeshi Yamada (Univ. of Tsukuba), Shoji Makino (Waseda Univ./Univ. of Tsukuba) SP2022-10 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Recently, acoustic scene classification using a beamformer with multi-channel signals as input has been proposed. Generally, prior information such as the direction of arrival of the target sound is necessary to generate the spatial filter of the beamformer. However, it is difficult to apply a beamformer as a pre-processing method because it is not obvious what kind of sound is of interest in a particular acoustic scene and in which direction the sound is located. We have devised an approach in which the networks of a spatial filter generator and classifier are concatenated and simultaneously optimized. The goal of this approach is to automatically learn what sounds to be focused on and automatically generate spatial filters to emphasize them,
without requiring any prior information such as the direction of arrival of the target sound or a reference signal. This paper proposes a loss function that incorporates the idea of the MVDR (Minimum Variance Distortionless Response) beamformer and verifies its effectiveness through experiments. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Acoustic Scene Classification / Neural Beamformer / Loss function / MVDR / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 81, SP2022-10, pp. 35-40, June 2022. |
Paper # |
SP2022-10 |
Date of Issue |
2022-06-10 (SP) |
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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SP2022-10 |
Conference Information |
Committee |
SP IPSJ-MUS IPSJ-SLP |
Conference Date |
2022-06-17 - 2022-06-18 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
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Paper Information |
Registration To |
SP |
Conference Code |
2022-06-SP-MUS-SLP |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Neural beamformer with automatic detection of notable sounds for acoustic scene classification |
Sub Title (in English) |
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Keyword(1) |
Acoustic Scene Classification |
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Neural Beamformer |
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Loss function |
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MVDR |
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1st Author's Name |
Sota Ichikawa |
1st Author's Affiliation |
University of Tsukuba (Univ. of Tsukuba) |
2nd Author's Name |
Takeshi Yamada |
2nd Author's Affiliation |
University of Tsukuba (Univ. of Tsukuba) |
3rd Author's Name |
Shoji Makino |
3rd Author's Affiliation |
Waseda University/University of Tsukuba (Waseda Univ./Univ. of Tsukuba) |
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Speaker |
Author-1 |
Date Time |
2022-06-17 15:00:00 |
Presentation Time |
120 minutes |
Registration for |
SP |
Paper # |
SP2022-10 |
Volume (vol) |
vol.122 |
Number (no) |
no.81 |
Page |
pp.35-40 |
#Pages |
6 |
Date of Issue |
2022-06-10 (SP) |
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