In this paper, we propose a robust voice activity detection (VAD) algorithm to effectively\ndistinguish speech from non-speech in various noisy environments. The proposed VAD utilizes\npower spectral deviation (PSD), using Teager energy (TE) to provide a better representation of the\nPSD, resulting in improved decision performance for speech segments. In addition, the TE-based\nlikelihood ratio and speech absence probability are derived in each frame to modify the PSD for\nfurther VAD.We evaluate the performance of the proposed VAD algorithm by objective testing in\nvarious environments and obtain better results that those attained by of the conventional methods.
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