On classification of environmental acoustic data using crowds

Shan Zhang, Aditya Vempaty, Susan E. Parks, Pramod K. Varshney

Research output: Chapter in Book/Entry/PoemConference contribution

4 Scopus citations

Abstract

In this work, we use crowds for acoustic classification of animal species in supervised and unsupervised manners. We demonstrate the effectiveness of the proposed triplet based crowdsourcing systems via actual experiments. Moreover, we propose a generalized 1-bit RPCA algorithm to further improve classification performance. The unique marriage of crowdsourcing and generalized 1-bit RPCA algorithm is shown to yield excellent performance for acoustic data classification.

Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5880-5884
Number of pages5
ISBN (Electronic)9781509041176
DOIs
StatePublished - Jun 16 2017
Event2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States
Duration: Mar 5 2017Mar 9 2017

Publication series

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

Other

Other2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
Country/TerritoryUnited States
CityNew Orleans
Period3/5/173/9/17

Keywords

  • acoustic data classification
  • animal specie classification
  • crowdsourcing
  • generalized 1-bit RPCA

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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