Subband wavelet signal denoising for voice activity detection

In this paper we propose a method for voice activity detection (VAD) in a speech signal recorded in the presence of noise. The so-called endpoint detection (EPD), i.e., detection of voice activity (speech) boundaries is very difficult if the signal is acquired in noisy environments. The proposed VAD method uses an additional stage of wavelet subband denoising. We compared this approach with other standard methods i.e.: zero-crossing rate and spectral entropy analysis. Additionally we present in this paper our basic results illustrating the main aim of this contribution, consisting in application of intelligent denoising strategies to various VAD algorithms.