An analysis/synthesis auditory filterbank based on an IIR implementation of the gammachirp.

Abstract

This paper proposes a new auditory filterbank that enables signal resynthesis from dynamic representations produced by a level-dependent auditory filterbank. The filterbank is based on a new IIR implementation of the gammachirp, which has been shown to be an excellent candidate for asymmetric, level-dependent auditory filters. Initially, the gammachirp filter is shown to be decomposed into a combination of a gammatone filter and an asymmetric function. The asymmetric function is excellently simulated with a minimum-phase IIR filter, named the “asymmetric compensation filter”. Then, two filterbank structures are presented each based on the combination of a gammatone filterbank and a bank of asymmetric compensation filters controlled by a signal level estimation mechanism. The inverse filter of the asymmetric compensation filter is always stable because the minimum-phase condition is satisfied. When a bank of inverse filters is utilized after the gammachirp analysis filterbank and the idea of wavelet transform is applied, it is possible to resynthesize signals with small time-invariant errors and achieve a guaranteed precision. This feature has never been accomplished by conventional active auditory filterbanks. The proposed analysis/synthesis gammachirp filterbank is expected to be useful in various applications where human auditory filtering has to be modeled.