Filter algorithm based on cochlear mechanics and neuron filter mechanism and application on enhancement of audio signals

Abstract

A filter algorithm based on cochlear mechanics and neuron filter mechanism is proposed from the view point of vibration. It helps to solve the problem that the non-linear amplification is rarely considered in studying the auditory filters. A cochlear mechanical transduction model is built to illustrate the audio signals processing procedure in cochlea, and then the neuron filter mechanism is modeled to indirectly obtain the outputs with the cochlear properties of frequency tuning and non-linear amplification. The mathematic description of the proposed algorithm is derived by the two models. The parameter space, the parameter selection rules and the error correction of the proposed algorithm are discussed. The unit impulse responses in the time domain and the frequency domain are simulated and compared to probe into the characteristics of the proposed algorithm. Then a 24-channel filter bank is built based on the proposed algorithm and applied to the enhancements of the audio signals. The experiments and comparisons verify that, the proposed algorithm can effectively divide the audio signals into different frequencies, significantly enhance the high frequency parts, and provide positive impacts on the performance of speech enhancement in different noise environments, especially for the babble noise and the volvo noise.