Abstract
The aim of speech stream detection is to capture the speech stream whose coming is random. The idea of using Higher Order Statistics (HOS) for speech stream detection is based on exploiting the Gaussian suppression that allows the separation of speech from the noise. HOS have inherent properties that make them well suited when dealing with a mixture of Gaussian and nonGaussian process. In addition, the HOS of speech signals have distinctive features that may be exploited to lead a better estimation and a more accurate discrimination between speech and noise. This paper explores the fourth order cumulants of speech signal and presents a new algorithm for speech stream detection. The considerable experimental results in which data comes from the real recorded on spot, show the method performs well.
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