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

• DOI: 10.3389/fnins.2023.1125210
• Publication Date: 2023-04-18T05:19:15Z
• Authors: Ying Xu; Samalika Perera; Yeshwanth Bethi; Saeed Afshar; André van Schaik
• Keywords: Benchmark (surveying); Feature (linguistics)

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