Investigating the Effect of Sound-Event Loudness on Crowdsourced Audio Annotations

Mark Cartwright, Justin Salamon, Ayanna Seals, Oded Nov, Juan Pablo Bello

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

Abstract

Audio annotation is an important step in developing machine-listening systems. It is also a time consuming process, which has motivated investigators to crowdsource audio annotations. However, there are many factors that affect annotations, many of which have not been adequately investigated. In previous work, we investigated the effects of visualization aids and sound scene complexity on the quality of crowdsourced sound-event annotations. In this paper, we extend that work by investigating the effect of sound-event loudness on both sound-event source annotations and sound-event proximity annotations. We find that the sound class, loudness, and annotator bias affect how listeners annotate proximity. We also find that loudness affects recall more than precision and that the strengths of these effects are strongly influenced by the sound class. These findings are not only important for designing effective audio annotation processes, but also for effectively training and evaluating machine-listening systems.

Original languageEnglish (US)
Title of host publication2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages341-345
Number of pages5
ISBN (Print)9781538646588
DOIs
StatePublished - Sep 10 2018
Event2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada
Duration: Apr 15 2018Apr 20 2018

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2018-April
ISSN (Print)1520-6149

Other

Other2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
CountryCanada
CityCalgary
Period4/15/184/20/18

Keywords

  • Audio annotations
  • Crowdsourcing
  • Machine listening
  • Sound event detection

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Cartwright, M., Salamon, J., Seals, A., Nov, O., & Bello, J. P. (2018). Investigating the Effect of Sound-Event Loudness on Crowdsourced Audio Annotations. In 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings (pp. 341-345). [8461833] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2018-April). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2018.8461833