A Robust Voice Activity Detection Algorithm in Nonstationary Noise

In this paper, we propose a new voice activity detection (VAD) algorithm to improve the speech detection robustness in nonstationary noisy environments. At front-end, Wiener filtering speech enhancement is adopted to suppress noise from noisy speech. Then, at back-end, the voice activity detector based on mel filter-bank spectral entropy is presented to distinguish speech from noise. We have evaluated system performance under noisy environments. Experimental results indicate that the proposed method is useful for achieving a considerable performance improvement for the VAD in nonstationary noise.