WAVE-DOMAIN ADAPTIVE FILTERING FOR ACOUSTIC HUMAN-MACHINE INTERFACES BASED ON WAVEFIELD ANALYSIS AND SYNTHESIS

摘要

Wave field synthesis and wave field analysis are attractive techniques for high-quality sound-field auralization and recording using loudspeaker arrays and microphone arrays. However, to utilize these techniques in multichannel acoustic interfaces, several challenges in signal processing have to be overcome in this new context, e.g., acoustic echo cancellation (AEC) to avoid acoustic feedback in full-duplex systems, interference cancellation on the recording side, and room compensation on the reproduction side. In traditional setups, these problems are tackled using adaptive filtering techniques in the time-frequency domain. In this paper, we present a novel and highly efficient framework for adaptive filtering in the wave domain by reconciling the flexibility of adaptive filtering and the underlying physics described by the acoustic wave equation. The new framework explicitly takes into account the spatial dimensions of the closely spaced loudspeakers and the microphone arrays. Experimental results with a 32-channel AEC verify the concept for both, simulated and actually measured room acoustics.