Auditory Representations of Acoustic Signals

Abstract

An analytically tractable framework is presented to describe neural processing in the early stages of the auditory system. Algorithms are developed to assess the integrity of the acoustic spectrum at all processing stages. The algorithms employ wavelet representations, multiresolution processing, and the method of convex projections to reconstruct close replica of the input stimulus. Reconstructions using natural speech sounds demonstrate minimal loss of information along the auditory pathway. Furthermore, close inspections of the final auditory patterns reveals spectral enhancements and noise suppression that have close perceptual correlates. Finally, the auditory representations are shown to be versatile for many applications, including automatic speech recognition and low bit-rate data compression.