Voice activity detection using global soft decision with mixture of Gaussian model
نویسندگان
چکیده
An improvement on the voice detection algorithm using global soft decision (GSD) is made in this paper. In GSD method, the speech and noise are modelled by the presumed probability density function, e.g. Gaussian pdf. We propose that the estimation and modelling of the signal is done in the domain of filterbank output which widely used in most speech processing applications. Since the output of filterbank is the weighted sum of outputs of several frequency bins, the signals can no longer be estimated using the Gaussian models but mixture of Gaussian models (GMM) in general. It is shown that the estimation of speech absence probability with GMM gives better performance.
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