Neural network-driven feedback cancellation
AssigneeStarkey Laboratories, Inc.
InventorsKelly Fitz, Carlos Renato Calcada Nakagawa, Tao Zhang
Life of this patent
Estimating the term…
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.
Claims20
A method of signal processing an input signal of a hearing device including a receiver, a microphone and an adaptive feedback cancellation filter to provide acoustic feedback cancellation on the input signal, the input signal being sound picked up by the microphone, the method comprising:
- training a neural network to identify acoustic features in a plurality of audio signals input to the neural network to extract the acoustic features from speech signals and predict target parameters for the plurality of audio signals, the plurality of audio signals including the input signal, including using a training set of inputs and outputs to adapt a network configuration to optimize ability to correctly predict the target parameters;
- and
- using the target parameters predicted by the trained network to govern adaptive behavior of the acoustic feedback cancellation on the input signal.
A hearing device, comprising:
- a microphone configured to receive an input signal, the input signal being sound picked up by the microphone;
- an adaptive feedback cancellation filter to provide acoustic feedback cancellation on the input signal;
- and
- a processor configured to process the input signal to correct for a hearing impairment of a wearer, the processor further configured to:
- train a neural network to identify acoustic features in a plurality of audio signals input to the neural network to extract the acoustic features from speech signals and predict target parameters for the plurality of audio signals, the plurality of audio signals including the input signal, including using a training set of inputs and outputs to adapt a network configuration to optimize ability to correctly predict the target parameters;
- and
- control acoustic feedback cancellation on the input signal based on using target parameters predicted by the trained neural network to govern adaptive behavior of the acoustic feedback cancellation on the input signal.
Dependencies are inferred from the claim text.