Noise injection for feedback cancellation with linear prediction

ABSTRACT Feedback oscillation is one of the major issues with hearing aids. An efficient way of feedback suppression is feedback cancellation, which uses an adaptive filter to estimate the feedback path. However, the feedback canceller suffers from the bias problem in the feedback path estimate. The recent progress suggests a feedback canceller with linear prediction of the desired signal in order to eliminate the bias when certain conditions are met. However, the bias still remains in many situations, for example when the input signal is voiced speech. Noise injection is investigated in this paper to help reduce the bias further and improve the system performance. Two nearly inaudible noises are proposed: a masking noise, which is tailored to the hearing-aid application, and a linear prediction based noise, which is especially efficient for feedback cancellation with linear prediction. Simulation results show that noise injection can further reduce the feedback estimation error by 1-4 dB and/or increase the stable gain by 3-4 dB, depending on the characteristics of the input signal