Beamformer improvement with increasing number of sensors

Abstract

The two-sensor frequency-banded minimum-variance beamformer (FBMVB) [Lockwood et al., J. Acoust. Soc. Am. 106, 2278 (1999)], shown to extract a target speech signal from multiple interfering speech sources, is extended to three and four sensors. The extended FBMVB retains the real-time computational advantages of the two-sensor FBMVB. Results from a battery of simulated and real acoustic environment tests suggest that the extended FBMVB offers better extraction of the target speech than the two-sensor FBMVB. Measuring the quality of extraction as signal-to-noise ratio gain and intelligibility-weighted signal-to-noise ratio gain, the extended FBMVB demonstrates performance improvements of 2–3 dB over the already high performance of the two-sensor FBMVB for most tests. In general, results suggest that the extended FBMVB is more robust with respect to crowded interferer settings and room reverberation.