This work is mainly focused on showing experimental results using a combination of two methods for noise compensation which are shown to be complementary: classical spectral subtraction algorithm and histogram equalization. While spectral subtraction is focused on the reduction of the additive noise in the spectral domain, histogram equalization is applied in the cepstral domain to compensate the remaining non-linear effects associated to channel distortion and additive noise. The estimation of the noise spectrum for the spectral subtraction method relies on a new algorithm for speech / non-speech detection (SND) based on order statistics. This SND classification is also used for dropping long speech pauses. Results on Aurora 2 and Aurora 3 are reported.