Paper Abstract and Keywords |
Presentation |
2017-07-20 13:40
Explicit Event Duration-Controlled BLSTM-HSMM Hybrid Model for Polyphonic Sound Event Detection Tomoki Hayashi (Nagoya Univ.), Shinji Watanabe (MERL), Tomoki Toda (Nagoya Univ.), Takaaki Hori, JonathanLe Roux (MERL), Kazuya Takeda (Nagoya Univ.) EA2017-2 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
This paper presents a new BLSTM-HSMM hybrid approach for polyphonic Sound Event Detection (SED). It builds upon a state-of-the-art sound event detection method which performs frame-by-frame detection using a bidirectional long short-term memory recurrent neural network (BLSTM), and incorporates a duration modeling technique based on a hidden semi-Markov model (HSMM). The proposed method makes it possible to model the duration of each sound event precisely and to perform sequence-by-sequence detection. Furthermore, to effectively reduce sound event insertion errors, we also introduce a binary-mask-based post-processing based on a sound activity detection (SAD) network. Using the DCASE2016 task2 Challenge dataset, we demonstrate that our proposed method outperformed conventional methods, such as non-negative matrix factorization (NMF) and standard BLSTM, also outperforming the best results reported in the DCASE2016 task 2 Challenge. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
sound event detection / BLSTM / HSMM / hybrid model / duration control / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 138, EA2017-2, pp. 9-14, July 2017. |
Paper # |
EA2017-2 |
Date of Issue |
2017-07-13 (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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EA2017-2 |
Conference Information |
Committee |
EA ASJ-H |
Conference Date |
2017-07-20 - 2017-07-21 |
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 |
2017-07-EA-H |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Explicit Event Duration-Controlled BLSTM-HSMM Hybrid Model for Polyphonic Sound Event Detection |
Sub Title (in English) |
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Keyword(1) |
sound event detection |
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BLSTM |
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HSMM |
Keyword(4) |
hybrid model |
Keyword(5) |
duration control |
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1st Author's Name |
Tomoki Hayashi |
1st Author's Affiliation |
Nagoya University (Nagoya Univ.) |
2nd Author's Name |
Shinji Watanabe |
2nd Author's Affiliation |
Mitsubishi electric research laboratories (MERL) |
3rd Author's Name |
Tomoki Toda |
3rd Author's Affiliation |
Nagoya University (Nagoya Univ.) |
4th Author's Name |
Takaaki Hori |
4th Author's Affiliation |
Mitsubishi electric research laboratories (MERL) |
5th Author's Name |
JonathanLe Roux |
5th Author's Affiliation |
Mitsubishi electric research laboratories (MERL) |
6th Author's Name |
Kazuya Takeda |
6th Author's Affiliation |
Nagoya University (Nagoya Univ.) |
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Speaker |
Author-1 |
Date Time |
2017-07-20 13:40:00 |
Presentation Time |
25 minutes |
Registration for |
EA |
Paper # |
EA2017-2 |
Volume (vol) |
vol.117 |
Number (no) |
no.138 |
Page |
pp.9-14 |
#Pages |
6 |
Date of Issue |
2017-07-13 (EA) |
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