VOICE ACTIVITY DETECTION WITH GENERALIZED GAMMA DISTRIBUTION

In this work, we model speech samples with the generalized Gamma distribution and evaluate the efficiency of such modelling for voice activity detection. Using a computationally inexpensive maximum likelihood approach, we employ the Bayesian Information Criterion for identifying the phoneme boundaries in noisy speech. 1