Voice activity detection using entropy in spectrum domain

Meysam Asgari, Abolghasem Sayadian, Mohsen Farhadloo, Elahe Abouie Mehrizi

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

9 Scopus citations

Abstract

In this paper we develop a voice activity detection algorithm based on entropy estimation of magnitude spectrum. In addition, the likelihood ratio test (LRT) is employed to determine a threshold to separate of speech segments from Nonspeech segments. The distributions of entropy magnitude of clean speech and noise signal are assumed to be Gaussian. The application of the concept of entropy to the speech detection problem is based on the assumption that the signal spectrum is more organized during speech segments than during noise segments. One of the main advantages of this method is that it is not very sensitive to the changes of noise level. Our simulation results show that the entropy based VAD is high performance in low Signal to Noise Ratio (SNR) conditions (SNR < 0 dB).

Original languageEnglish (US)
Title of host publicationProceedings of the 2008 Australasian Telecommunication Networks and Applications Conference, ATNAC 2008
Pages407-410
Number of pages4
DOIs
StatePublished - 2008
Externally publishedYes
Event2008 Australasian Telecommunication Networks and Applications Conference, ATNAC 2008 - Adelaide, SA, Australia
Duration: Dec 7 2008Dec 10 2008

Publication series

NameProceedings of the 2008 Australasian Telecommunication Networks and Applications Conference, ATNAC 2008

Conference

Conference2008 Australasian Telecommunication Networks and Applications Conference, ATNAC 2008
CountryAustralia
CityAdelaide, SA
Period12/7/0812/10/08

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Communication

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