A statistical model-based voice activity detection

In this letter, we develop a robust voice activity detector (VAD) for the a pplication to variable-rate speech coding. The developed VAD employs the de cision-directed parameter estimation method for the likelihood ratio test. In addition, we propose an effective hang-over scheme which considers the p revious observations by a first-order Markov process modeling of speech occ urrences. According to our simulation results, the proposed VAD shows signi ficantly better performances than the G.729B VAD in low signal-to-noise rat io (SNR) and vehicular noise environments.