Joint analysis of acoustic events and scenes based on multitask learning

Noriyuki Tonami, Keisuke Imoto, Masahiro Niitsuma, Ryosuke Yamanishi, Yoichi Yamashita

研究成果: Conference contribution

7 被引用数 (Scopus)

抄録

Acoustic event detection and scene classification are major research tasks in environmental sound analysis, and many methods based on neural networks have been proposed. Conventional methods have addressed these tasks separately; however, acoustic events and scenes are closely related to each other. For example, in the acoustic scene "office, " the acoustic events "mouse clicking" and "keyboard typing" are likely to occur. In this paper, we propose multitask learning for joint analysis of acoustic events and scenes, which shares the parts of the networks holding information on acoustic events and scenes in common. By integrating the two networks, we also expect that information on acoustic scenes will improve the performance of acoustic event detection. Experimental results obtained using TUT Sound Events 2016/2017 and TUT Acoustic Scenes 2016 datasets indicate that the proposed method improves the performance of acoustic event detection by 10.66 percentage points in terms of the F-score, compared with a conventional method based on a convolutional recurrent neural network.

本文言語English
ホスト出版物のタイトル2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ページ338-342
ページ数5
ISBN(電子版)9781728111230
DOI
出版ステータスPublished - 2019 10
外部発表はい
イベント2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2019 - New Paltz, United States
継続期間: 2019 10 202019 10 23

出版物シリーズ

名前IEEE Workshop on Applications of Signal Processing to Audio and Acoustics
2019-October
ISSN(印刷版)1931-1168
ISSN(電子版)1947-1629

Conference

Conference2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2019
国/地域United States
CityNew Paltz
Period19/10/2019/10/23

ASJC Scopus subject areas

  • 電子工学および電気工学
  • コンピュータ サイエンスの応用

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