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.