Abstract: Disclosed herein, among other things, are apparatus and methods for neural network-driven feedback cancellation for hearing assistance devices. Various embodiments include a method of signal processing an input signal in a hearing assistance device to mitigate entrainment, the hearing assistance device including a receiver and a microphone. The method includes performing neural network processing to identify acoustic features in a plurality of audio signals and predict target outputs for the plurality of audio signals, and using the trained neural network to control acoustic feedback cancellation of the input signal.

Abstract: Disclosed herein, among other things, are apparatus and methods for neural network-driven feedback cancellation for hearing assistance devices. Various embodiments include a method of signal processing an input signal in a hearing assistance device to mitigate entrainment, the hearing assistance device including a receiver and a microphone. The method includes performing neural network processing to identify acoustic features in a plurality of audio signals and predict target outputs for the plurality of audio signals, and using the trained neural network to control acoustic feedback cancellation of the input signal.

Abstract: Disclosed herein, among other things, are apparatus and methods for neural network-driven feedback cancellation for hearing assistance devices. Various embodiments include a method of signal processing an input signal in a hearing assistance device to mitigate entrainment, the hearing assistance device including a receiver and a microphone. The method includes performing neural network processing to identify acoustic features in a plurality of audio signals and predict target outputs for the plurality of audio signals, and using the trained neural network to control acoustic feedback cancellation of the input signal.

Abstract: The present subject matter can improve robustness of performance of acoustic feedback cancellation in the presence of strong acoustic disturbances. In various embodiments, an optimization criterion determined to enhance robustness of an adaptive feedback canceller in an audio device against disturbances in an incoming audio signal can be applied such that the adaptive feedback canceller remains in a converged state in response to presence of the disturbances.

Abstract: Disclosed herein, among other things, are apparatus and methods for neural network-driven feedback cancellation for hearing assistance devices. Various embodiments include a method of signal processing an input signal in a hearing assistance device to mitigate entrainment, the hearing assistance device including a receiver and a microphone. The method includes performing neural network processing to identify acoustic features in a plurality of audio signals and predict target outputs for the plurality of audio signals, and using the trained neural network to control acoustic feedback cancellation of the input signal.

Abstract: Disclosed herein, among other things, are apparatus and methods for tonality-driven feedback canceler adaptation for hearing devices. Various embodiments include a method of signal processing an input signal in a hearing device to mitigate entrainment, the hearing device including a receiver and a microphone. The method includes detecting strength of tonality of the input signal by estimating a second derivative of subband phase of the input signal, and adjusting parameters of an adaptive feedback canceler of the hearing device based on the detected tonality.

Abstract: The present subject matter can improve robustness of performance of acoustic feedback cancellation in the presence of strong acoustic disturbances. In various embodiments, an optimization criterion determined to enhance robustness of an adaptive feedback canceller in an audio device against disturbances in an incoming audio signal can be applied such that the adaptive feedback controller remains in a converged state in response to presence of the disturbances.

Abstract: Disclosed herein, among other things, are apparatus and methods for neural network-driven feedback cancellation for hearing assistance devices. Various embodiments include a method of signal processing an input signal in a hearing assistance device to mitigate entrainment, the hearing assistance device including a receiver and a microphone. The method includes performing neural network processing to identify acoustic features in a plurality of audio signals and predict target outputs for the plurality of audio signals, and using the trained neural network to control acoustic feedback cancellation of the input signal.

Abstract: Disclosed herein, among other things, are apparatus and methods for tonality-driven feedback canceler adaptation for hearing devices. Various embodiments include a method of signal processing an input signal in a hearing device to mitigate entrainment, the hearing device including a receiver and a microphone. The method includes detecting strength of tonality of the input signal by estimating a second derivative of subband phase of the input signal, and adjusting parameters of an adaptive feedback canceler of the hearing device based on the detected tonality.