Towards Low-Power On-chip Auditory Processing

Abstract

Machine perception is a difficult problem both from a practical or implementation point of view as well as from a theoretical or algorithm point of view. Machine perception systems based on biological perception systems show great promise in many areas but they often have processing requirements and/or data flow requirements that are difficult to implement, especially in small or low-power systems. We propose a system design approach that makes it possible to implement complex functionality using cooperative analog-digital signal processing to lower-power requirements dramatically over digital-only systems, as well as provide an architecture facilitating the development of biologically motivated perception systems. We show the architecture and application development approach. We also present several reference systems for speech recognition, noise suppression, and audio classification.