Event-driven spectrotemporal feature extraction and classification using a silicon cochlea model

Event-driven spectrotemporal feature extraction and classification using a silicon cochlea model

Blog Article

This paper presents a reconfigurable digital implementation of an event-based Cleaning binaural cochlear system on a Field Programmable Gate Array (FPGA).It consists of a pair of the Cascade of Asymmetric Resonators with Fast Acting Compression (CAR-FAC) cochlea models and Toddler leaky integrate-and-fire (LIF) neurons.Additionally, we propose an event-driven SpectroTemporal Receptive Field (STRF) Feature Extraction using Adaptive Selection Thresholds (FEAST).It is tested on the TIDIGTIS benchmark and compared with current event-based auditory signal processing approaches and neural networks.