Robust Voice Activity Detection Based on Spectral Entropy and Two-Stage Mel-Warped Wiener Filtering

This paper proposes a novel voice activity detection (VAD) algorithm to improve the speech detection robustness in noisy environments. In the proposed algorithm, two-stage mel-warped Wiener filter is introduced to improve the performance of voice activity detector based on spectral entropy. Then an improved decision rule based on spectral entropy was derived. We have evaluated system performance under noisy environments using NOISEX-92 database and recorded speech signals. Experimental results indicate that our approach exhibits considerable improvements in the degraded environment.