Feature analysis and selection for acoustic event detection

Xiaodan Zhuang, Xi Zhou, Thomas S Huang, Mark Allan Hasegawa-Johnson

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

Abstract

Speech perceptual features, such as Mel-frequency Cepstral Coefficients (MFCC), have been widely used in acoustic event detection. However, the different spectral structures between speech and acoustic events degrade the performance of the speech feature sets. We propose quantifying the discriminative capability of each feature component according to the approximated Bayesian accuracy and deriving a discriminative feature set for acoustic event detection. Compared to MFCC, feature sets derived using the proposed approaches achieve about 30% relative accuracy improvement in acoustic event detection.

Original languageEnglish (US)
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages17-20
Number of pages4
DOIs
StatePublished - Sep 16 2008
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: Mar 31 2008Apr 4 2008

Publication series

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

Other

Other2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
CountryUnited States
CityLas Vegas, NV
Period3/31/084/4/08

Keywords

  • Acoustic event detection
  • Bayesian Accuracy
  • Feature Selection
  • Hidden Markov Models

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Zhuang, X., Zhou, X., Huang, T. S., & Hasegawa-Johnson, M. A. (2008). Feature analysis and selection for acoustic event detection. In 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP (pp. 17-20). [4517535] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2008.4517535