  Speech activity detection (SAD) is an essential component for a variety of
speech processing applications. It has been observed that performances of
various speech based tasks are very much dependent on the efficiency of the
SAD. In this paper, we have systematically reviewed some popular SAD techniques
and their applications in speaker recognition. Speaker verification system
using different SAD technique are experimentally evaluated on NIST speech
corpora using Gaussian mixture model- universal background model (GMM-UBM)
based classifier for clean and noisy conditions. It has been found that two
Gaussian modeling based SAD is comparatively better than other SAD techniques
for different types of noises.
