Performance of adaptive beamformers for extracting audio signals

The need to extract a single audio signal of interest from a multi-source and noisy environment is common across many disciplines. Adaptive beamforming, due to its superior interference rejection and noise suppression, is a preferred processing technique for obtaining high quality audio in noisy environments. In this paper, we compare the performances of two different types of adaptive beamformers for the purpose of extracting audio signals. One of the beamformers is the robust Capon beamformer (RCB) where the beamforming part is carried out in the frequency domain, resulting in low computational complexity but relatively high latency. The other beamformer is the block constrained least mean square beamformer (BCLMSB) where the beamforming part is carried out in the time domain. It has relatively higher computational cost but no latency. The performances of these two adaptive beamformers are evaluated in terms of fidelity of the beamformer output and robustness of the system under various conditions.