Application of Gammachirp Auditory Filter as a Continuous Wavelet Analysis

TL;DR

This paper introduces a novel continuous wavelet analysis method using the gammachirp auditory filter, designed to mimic cochlear spectral properties, and compares its effectiveness with existing wavelet families in speech signal analysis.

Contribution

It develops and applies a gammachirp-based wavelet as a new analytical tool for speech signals, demonstrating its comparable performance to established wavelet families.

Findings

Gammachirp wavelet provides spectral analysis results similar to Morlet and Mexican Hat wavelets.

The method effectively analyzes speech signals with cochlear-like spectral properties.

The gammachirp wavelet offers a biologically inspired alternative for auditory signal processing.

Abstract

This paper presents a new method on the use of the gammachirp auditory filter based on a continuous wavelet analysis. The gammachirp auditory filter is designed to provide a spectrum reflecting the spectral properties of the cochlea, which is responsible for frequency analysis in the human auditory system. The impulse response of the theoretical gammachirp auditory filter that has been developed by Irino and Patterson can be used as the kernel for wavelet transform which approximates the frequency response of the cochlea. This study implements the gammachirp auditory filter described by Irino as an analytical wavelet and examines its application to a different speech signals. The obtained results will be compared with those obtained by two other predefined wavelet families that are Morlet and Mexican Hat. The results show that the gammachirp wavelet family gives results that are comparable to ones obtained by Morlet and Mexican Hat wavelet family.