US 11,985,482 B2
Neural network-driven feedback cancellation
Kelly Fitz, Eden Prairie, MN (US); Carlos Renato Calcada Nakagawa, Eden Prairie, MN (US); and Tao Zhang, Eden Prairie, MN (US)
Assigned to Starkey Laboratories, Inc., Eden Prairie, MN (US)
Filed by Starkey Laboratories, Inc., Eden Prairie, MN (US)
Filed on Mar. 13, 2023, as Appl. No. 18/120,665.
Application 18/120,665 is a continuation of application No. 17/249,581, filed on Mar. 5, 2021, granted, now 11,606,650.
Application 17/249,581 is a continuation of application No. 15/133,896, filed on Apr. 20, 2016, abandoned.
Prior Publication US 2023/0328463 A1, Oct. 12, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. H04R 25/00 (2006.01); H04R 3/00 (2006.01)
CPC H04R 25/507 (2013.01) [H04R 3/005 (2013.01); H04R 25/453 (2013.01); H04R 25/558 (2013.01); H04R 2225/023 (2013.01)] 20 Claims
OG exemplary drawing
 
1. 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 trained neural network to extract acoustic features from the input signal and predict target parameters for the plurality of audio signals, the plurality of audio signals including the input signal; and
using the target parameters predicted by the trained neural network to govern adaptive behavior of the acoustic feedback cancellation on the input signal.