Audio content description with wavelets and neural nets

Stephan Rein, Martin Reisslein, Thomas Sikora

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

Abstract

Precision audio content description is one of the key components of next generation internet multimedia search machines. We examine the usability of a combination of 39 different wavelets and three different types of neural nets for precision audio content, description. More specifically, we develop a novel wavelet dispersion measure that measures obtained ranks of wavelet coefficients. Our dispersion measure in conjunction with a probabilistic radial basis neural network trained by only three independent example sets obtains a success rate of approximately 78% in identifying unknown complex classical music movements.

Original languageEnglish (US)
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume4
StatePublished - 2004
EventProceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada
Duration: May 17 2004May 21 2004

Other

OtherProceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing
CountryCanada
CityMontreal, Que
Period5/17/045/21/04

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Acoustics and Ultrasonics

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