FPGA Implementation of the CAR Model of the Cochlea

TL;DR

This paper presents a real-time FPGA implementation of the CAR model of the cochlea, capturing its nonlinear and frequency discrimination properties for advanced machine-hearing applications.

Contribution

It introduces a hardware implementation of the CAR-FAC cochlear model on FPGA, enabling real-time sound processing with high section count and biological fidelity.

Findings

Implemented up to 1224 cochlear sections on FPGA

Achieved real-time sound processing capabilities

Replicated key cochlear characteristics such as dynamic range and tuning

Abstract

The front end of the human auditory system, the cochlea, converts sound signals from the outside world into neural impulses transmitted along the auditory pathway for further processing. The cochlea senses and separates sound in a nonlinear active fashion, exhibiting remarkable sensitivity and frequency discrimination. Although several electronic models of the cochlea have been proposed and implemented, none of these are able to reproduce all the characteristics of the cochlea, including large dynamic range, large gain and sharp tuning at low sound levels, and low gain and broad tuning at intense sound levels. Here, we implement the Cascade of Asymmetric Resonators (CAR) model of the cochlea on an FPGA. CAR represents the basilar membrane filter in the Cascade of Asymmetric Resonators with Fast-Acting Compression (CAR-FAC) cochlear model. CAR-FAC is a neuromorphic model of hearing based on a pole-zero filter cascade model of auditory filtering. It uses simple nonlinear extensions of conventional digital filter stages that are well suited to FPGA implementations, so that we are able to implement up to 1224 cochlear sections on Virtex-6 FPGA to process sound data in real time. The FPGA implementation of the electronic cochlea described here may be used as a front-end sound analyser for various machine-hearing applications.