Acoustic feedback is a well-known phenomenon in hearing aids. Under certain conditions, it causes the so-called howling effect, which is highly annoying for the hearing aid user and limits the maximum amplification of the hearing aid. The standard adaptive feedback cancellation algorithms suffer from a biased adaptation if the input signal is spectrally colored or tonal, as it is for speech and music signals. Due to this bias distortion artifacts (entrainment) are generated. In this letter, we present a method to detect tonal, high correlated parts of the input signal. In particular, the method is able to distinguish between correlation resulting from the input signal and from feedback path changes. A subband feedback cancellation system which applies decorrelation methods is the basis for the proposed method. Additionally, we suggest to use the correlation detection to increase the performance of the mentioned feedback cancellation system. The performance is measured by preventing entrainment and reacting to feedback path changes.

Acoustic feedback is a well-known phenomenon in hearing aids. Under certain conditions it causes the so-called howling effect, which is highly annoying for the hearing aid user and limits the maximum amplification of the hearing aid. The standard adaptive feedback cancellation algorithms suffer from a biased adaptation if the input signal is spectrally colored, as it is for speech and music signals. Due to this bias distortion artifacts (entrainment) are generated. In this paper, we present a sub-band feedback cancellation system which combines decorrelation methods with a new realization of a known non-parametric variable step size. To apply this step size in the context of adaptive feedback cancellation, a method to estimate the signal power of the desired input signal, i.e., without feedback, is necessary. A major part of this paper is spent with the theoretical derivation of this estimate. Furthermore, the complete system is evaluated extensively for several speech and music signals as well as for different feedback scenarios in simulations with feedback paths measured in concrete applications as well as for real-time simulations with hearing aid dummies. Both use hearing loss compensation methods as applied in physical hearing aids. The performance is measured in terms of being able to prevent entrainment and to react to feedback path changes. For both simulation setups the system shows a good performance with respect to the two performance measures. Furthermore, the overall feedback cancellation method relies only on few parameters, shows a low computational complexity, and therefore has a strong practical relevance.

Standard adaptive feedback cancellation algorithms in hearing aids suffer from a biased adaptation if the input signal is spectrally colored, as it is for tonal signals, like music. Due to that, distortion artifacts (entrainment) are generated. In this paper, a sub-band feedback cancellation system is presented combined with an adaptation control to deal with those signals. Two control concepts for determining the variable step sizes [1, 2], known from general adaptive filter algorithms, are theoretically and practically analyzed and evaluated for an application to feedback cancellation. For feedback cancellation the control is combined with known methods to reduce the bias, such as prediction error filtering or frequency shifting. Based on this combination, a completely new setup for feedback cancellation is proposed. It relies entirely on signals accessible in real systems, shows a low computational complexity, and therefore has a strong practical relevance.