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Summary form only given. In adaptive filtering, undetected noise bursts often disturb the adaptation and may lead to instabilities and divergence of the adaptive filter. The sensitivity against noise bursts increases with the convergence speed of the adaptive filter and limits the performance of signal processing methods where fast convergence is required. Typical applications which are sensitive against noise bursts are adaptive beamforming for audio signal acquisition or acoustic echo cancellation, where noise bursts are frequent due to undetected double-talk. In this paper, we apply double-talk resistant adaptive filtering (Gaensler (1998)) using a nonlinear optimization criterion to adaptive beamforming in the discrete Fourier transform domain for bin-wise adaptation controls. We show the efficiency of double-talk resilient adaptive filtering for a generalized sidelobe canceller for speech and audio signal acquisition. The improved robustness leads to faster convergence, to higher noise reduction, and to a better output signal quality in turn.