Adaptive Feedback Cancellation With Band-Limited LPC Vocoder in Digital Hearing Aids

Abstract

Abstract-Feedback oscillation is one of the major issues with hearing aids. An effective way of feedback suppression is adaptive feedback cancellation, which uses an adaptive filter to estimate the feedback path. However, when the external input signal is correlated with the receiver input signal, the estimate of the feedback path is biased. This so-called "bias problem" results in a large modeling error and a cancellation of the desired signal. This paper proposes a band-limited linear predictive coding based approach to reduce the bias. The idea is to replace the hearing-aid output with a synthesized signal, which sounds perceptually the same as or similar to the original signal but is statistically uncorrelated with the external input signal at high frequencies where feedback oscillation usually occurs. Simulation results show that the proposed algorithm can effectively reduce the bias and the misalignment between the real and the estimated feedback path. When combined with filtered-X adaptation in the feedback canceller, this approach reduces the misalignment even further. Index Terms-Adaptive feedback cancellation (AFC), hearing aids, linear predictive coding (LPC).

On new efficient μ ‐law‐based method for feedback compensation in hearing aids

“…The update of the coefficients of the adaptive filter according to the APL algorithm can be expressed as [9] w(n + 1) =ŵ(n) + Y f (n)e f (n) 2 Y f,T (n)Y f (n)e f (n) 2 Y f (n)e f (n) (4) where e f (n) and y f (n) represents the filtered error and the microphone signal obtained using prediction error filter as suggested in [1]. Now, the update scheme considering the proportionate gain factor pertaining to each tap of the adaptive filter is written as [10] w(n + 1) =ŵ(n) + R(n)e f (n) 2 Y f,T (n)R(n)e f (n) 2 R(n)e f (n) (5) where R(n) is obtained as…”

“…The microphone signal u ( n ) is the sum of the feedback signal v ( n ) and the desired incoming signal x ( n ) as shown in Fig. 1 [1]. An adaptive filter generates an estimate of the feedback signal , which is subtracted from the microphone signal to generate an error signal e ( n ).…”

“…The update of the coefficients of the adaptive filter according to the APL algorithm can be expressed as [9] where e f ( n ) and y f ( n ) represents the filtered error and the microphone signal obtained using prediction error filter as suggested in [1].…”

“…However, the correlation between the desired incoming signal and the speaker signal results in biased estimation of the feedback signal. In the literature, several techniques such as the prediction error method employing band‐limited linear predictive coding (LPC) vocoder [1], improved prediction error filter [2], pitch‐based formant estimation AFC [3], probe noise [4] and two microphone [5] approach have been proposed to tackle the problem of bias.…”

Mean square performance evaluation in frequency domain for an improved adaptive feedback cancellation in hearing aids

“…Feedback cancellation methods, such as feedback cancella-15 tion using adaptive filters, are based on estimating the true feedback path to generate an estimate of the original feedback signal. Among many such approaches, band-limited linear predictive coding (LPC)-based adaptive feedback cancellation (AFC) system stands out due to its effectiveness in efficiently reducing the high-frequency bias in the estimate of the original feedback path 20 [6]. However, since a small amount of bias still persists, introduction of probe noise signal in the feedback estimation path can further reduce the bias [7].…”