Neuromorphic acoustic sensing using an adaptive microelectromechanical cochlea with integrated feedback

Many speech processing systems struggle in conditions with low signal-to-noise ratios and in changing acoustic environments. Adaptation at the transduction level with integrated signal processing could help to address this; in human hearing, transduction and signal processing are integrated and can be adaptively tuned for noisy conditions. Here we report a microelectromechanical cochlea as a bio-inspired acoustic sensor with integrated signal processing functionality. Real-time feedback is used to tune the sensing and processing properties, and dynamic switching between linear and nonlinear characteristics improves the detection of signals in noisy conditions, increases the sensor dynamic range and enables adaptation to changing acoustic environments. The transition to nonlinear behaviour is attributed to a Hopf bifurcation and we experimentally validate its dependence on sensor and feedback parameters. We also show that output-signal coupling between two coupled sensors can increase the frequency coverage. A microelectromechanical cochlea, which consists of a bio-inspired acoustic sensor with a thermo-mechanical feedback mechanism, exhibits active auditory sensing, allowing the sensor to adapt its properties to different acoustic environments.

Automated summary

This article discusses a bio-inspired acoustic sensor with integrated signal processing functionality, which can adaptively adjust its sensing and processing properties in low signal-to-noise ratio and changing acoustic environments to improve the detection of signals in noisy conditions.