Unbiased adaptive feedback cancellation in hearing aids by closed-loop identification

Abstract

Hearing aid users often suffer from feedback which causes "howling" and limits the maximum stable gain. The direct method of adaptive feedback cancellation is widely used to mitigate feedback, however it is less effective for high forward path gains due to the inherent bias in the feedback path estimate. This bias can be reduced at the expense of artificial delays which can potentially introduce pre-echo and "comb filter" effects. The direct method also tends to cancel tonal audio signals such as alarms and music. We propose using a system identification method in closed-loop for unbiased feedback cancellation which does not possess the negative characteristics manifested by the direct method, but uses an identification signal. The two-stage method which employs two adaptive filters, one to identify the entire closed-loop, and another to extract the feedback path response was the preferred unbiased method due to its low computation and good feedback identification particularly during "howling." This paper presents the theory of the proposed new method, and computer simulations which demonstrate its advantages over the widely used direct method.