The occlusion effect is a common complaint from users of hearing aids with narrow or unvented earmolds. This phenomenon makes the user hear his own voice muffled. In the scientific literature, fixed and adaptive controllers have been proposed for occlusion effect reduction. This work proposes a cepstral method to estimate the stable optimal solution for feedforward occlusion cancellation and a fixed controller that utilizes this estimate to reduce the occlusion effect in hearing aids. The cepstral method operates on a feedback structure at a calibration process. Simulations have shown that the performance of the cepstral method improves as the length of the signal uttered by the hearing aid user increases, resulting in estimates with average normalized misalignment less than -19 and -34 dB for signals lasting 1.5 and 5 s. The estimates are significantly more accurate below 500 Hz, which is the frequency range common to the occlusion effect. In addition, results have pointed out that the controller attenuated the occlusion effect, averagely decreasing by 0.17 dB the distortion power and increasing by 0.13 the objective perceptual quality MOS-LQO score.
This work presents a theoretical analysis of the prediction-error method-based adaptive feedback canceller in hearing aid applications. The studied scene takes into account the occlusion effect caused by the partial or complete closing of the ventilation opening. Such a situation may occur in high gain applications to avoid undesired whistling. Deterministic recursive equations and steady-state conditions were derived for the mean weight behaviour of the predictor and the adaptive filter. The expected theoretical predictions were compared to Monte Carlo simulations, showing very accurate agreement. The simulation results suggest the steady-state performance of this feedback canceller is not affected by the occlusion effect, however the occlusion is still perceived, being annoying to the user.
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