Joint analysis of acoustic events and scenes based on multitask learning

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages338-342
Number of pages5
ISBN (Electronic)9781728111230
DOIs
Publication statusPublished - 2019 Oct
Externally publishedYes
Event2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2019 - New Paltz, United States
Duration: 2019 Oct 202019 Oct 23

Publication series

NameIEEE Workshop on Applications of Signal Processing to Audio and Acoustics
Volume2019-October
ISSN (Print)1931-1168
ISSN (Electronic)1947-1629

Conference

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

Keywords

  • Acoustic event detection
  • acoustic scene classification
  • convolutional recurrent neural network
  • multitask learning

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications

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