Abstract
The adaptive beamformer approach for noise reduction in hearing aids is known to be very successful in anechoic chambers and other experimental situations, but the performance decreases rapidly in realistic environments. In order to optimize the adaptive beamformer for everyday use, the algorithm was analyzed by means of a novel theoretical approach, which estimates the performance as a function of several acoustic and design parameters. According to our findings, adaptive filters of at least 50 ms in length have to be used in order to achieve a gain in signal-to-noise ratio of approximately 4 to 6 dB in ordinary office-sized rooms with typical reverberation times of around 0.4 s. Furthermore, a reliable target signal detection algorithm is necessary in order to prevent the adaptation of the filter in the presence of strong target signals. An optimized version of the adaptive beamformer has been implemented in real time on a TMS320C30 digital signal processing system. Preliminary results of intelligibility tests will be presented. [Work supported by the Swiss National Research Foundation.]
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