A new approach for robust realtime Voice Activity Detection using spectral pattern

In this paper a Voice Activity Detection approach is proposed which applies a voting algorithm to decide on the existence of speech in audio signal. For this purpose, the proposed approach uses three different short time features along with the pattern of spectral peaks of every frame. Spectral peaks pattern is appropriate for determining vowel sounds in speech signal even in the presence of noise. Therefore this measure can be applicable in voice activity detection in which the vowels characterize the speech signal. Experiments show that incorporating this measure along with our recently proposed approach for VAD, will improve the results of the algorithm considerably while imposing little computational overhead. The proposed approach is evaluated on different datasets with various noises and SNR levels and satisfying results are achieved.