Analysis method to approximate the spectral density of noises

Usual noise models represent sounds with filtered white noise, and extract only the spectral envelope from the sounds analyzed. Psychoacoustic experiments have shown the ability of humans to discriminate noise bands with different spectral densities. This property may be taken into account for the mathematical representation of noises. We propose an original method to approximate this new parameter. The limitations of the discrete short-term transform lead us to consider a new approach. This technique is based on statistical studies of the intensity fluctuations which are theoretically related to the spectral density. An algorithm is detailed and its parameters are discussed. Experiments show the quality and the limitations of this method. Although it may be improved, this estimation technique is accurate enough to be applied in a complete analysis/synthesis model for noisy sounds.