Analysis, Design, and Evaluation of Acoustic Feedback Cancellation Systems for Hearing Aids - A Novel Approach to Unbiased Feedback Estimation

Acoustic feedback problems occur when the output loudspeaker signal of an audio system is partly returned to the input microphone via an acoustic coupling through the air. This problem often causes significant performance degradations in applications such as public address systems and hearing aids. In the worst case, the audio system becomes unstable and howling occurs. In this work, first we analyze a general multiple microphone audio processing system, where a cancellation system using adaptive filters is used to cancel the effect of acoustic feedback. We introduce and derive an accurate approximation of a frequency domain measure—the power transfer function—and show how it can be used to predict the convergence rate, system stability bound, and the steady-state behavior of the entire cancellation system across time and frequency without knowing the true acoustic feedback paths. This power transfer function method is also applicable to an acoustic echo cancellation system with a similar structure. Furthermore, we consider the biased estimation problem, which is one of the most challenging problems for state-of-the-art acoustic feedback cancellation systems. A commonly known approach to deal with the biased estimation problem is adding a probe noise signal to the loudspeaker signal and base the estimation on that. This approach is particularly promising, since it can be shown that, in theory, the biased estimation problem can be completely eliminated. However, we analyze a traditional probe noise approach and conclude that it can not work in most acoustic feedback cancellation systems in practice, due to the very low convergence rate of the adaptive cancellation system when using low level and inaudible probe noise signals. We propose a novel probe noise approach to solve the biased estimation problem in acoustic feedback cancellation for hearing aids. It utilizes a probe noise signal which is generated with a specific characteristic so that it can facilitate an unbiased adaptive filter estimation with fast tracking of feedback path variations/changes despite its low signal level. We show in a hearing aid application that whereas the traditional and stateof-the-art acoustic feedback cancellation systems fail with significant sound distortions and howling as consequences, the new probe noise approach is able to remove feedback artifacts caused by the feedback path change in no more than a few hundred milliseconds.