Towards Next-Generation Auditory Information Processing: A Neuromorphic Approach

Hearing is a vivid part of our conscious lives. Driven by recent advances in artificial intelligence (AI), the capability of machine hearing systems has improved by leaps and bounds over the last decade. The increased capability also comes along with challenges to efficiently, rapidly, and reliably process sound signals. With an ever-growing demand for human-computer auditory interfaces, these challenges are expected to be exacerbated. By harnessing the findings and insights from neuroscience studies, the interdisciplinary neuromorphic computing research offers immense opportunities for building brain-inspired auditory systems for machine hearing. In this talk, Dr WU will present his recent research outcomes on neuromorphic auditory information processing that is grounded on the brain-inspired spiking neural networks (SNNs). In particular, Dr WU will present the technology breakthroughs in: 1) auditory neural codes that can efficiently and effectively encode sound signals; 2) task-specific neural architectures that grounded on the pre-existing neural structures.