Neuromorphic acoustic sensing using an adaptive microelectromechanical cochlea with integrated feedback

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