Presentation 2021-07-16
Sound event detection based on complementary-label learning
Keigo Wakayama, Shoichiro Saito,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Sound Event Detection (SED) is an important research field that can be applied to smart cities, and etc. SED estimate the start and end of events in addition to the presence or absence of events in acoustic data. To improve the estimation accuracy, a lot of labeled data is required, but it is difficult to assign a lot of correct labels. Considering effectively utilizing the data with the complementary label (class that is not the correct answer), therefore, we propose a method to realize SED by learning model from complementary labeled data. The effectiveness of the method is confirmed experimentally.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Sound Event Detection / Audio Tagging / Weakly-supervised learning / Complementary-label learning
Paper # EA2021-17
Date of Issue 2021-07-08 (EA)

Conference Information
Committee EA / ASJ-H
Conference Date 2021/7/15(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English) Engineering/Electro Acoustics, Psychological and Physiological Acoustics, Speech, Musical Acoustics, Education in Acoustics, and Related Topics
Chair Yoshinobu Kajikawa(Kansai Univ.)
Vice Chair Kenichi Furuya(Oita Univ.) / Shoichi Koyama(Univ. of Tokyo)
Secretary Kenichi Furuya(NTT) / Shoichi Koyama(RitsumeikanUniv.)
Assistant Yukou Wakabayashi(Tokyo Metropolitan Univ.) / Tatsuya Komatsu(LINE)

Paper Information
Registration To Technical Committee on Engineering Acoustics / Auditory Research Meeting
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Sound event detection based on complementary-label learning
Sub Title (in English)
Keyword(1) Sound Event Detection
Keyword(2) Audio Tagging
Keyword(3) Weakly-supervised learning
Keyword(4) Complementary-label learning
1st Author's Name Keigo Wakayama
1st Author's Affiliation Nippon Telegraph and Telephone Corporation(NTT)
2nd Author's Name Shoichiro Saito
2nd Author's Affiliation Nippon Telegraph and Telephone Corporation(NTT)
Date 2021-07-16
Paper # EA2021-17
Volume (vol) vol.121
Number (no) EA-112
Page pp.pp.77-82(EA),
#Pages 6
Date of Issue 2021-07-08 (EA)