Microphone Array Geometries for Horizontal Spatial Audio Object Capture With Beamforming

Abstract

Microphone array beamforming can be used to enhance and separate sound sources, with applications in the capture of object-based audio. Many beamforming methods have been proposed and assessed against each other. However, the effects of compact microphone array design on beamforming performance have not been studied for this kind of application. This study investigates how to maximize the quality of audio objects extracted from a horizontal sound field by filter-and-sum beamforming, through appropriate choice of microphone array design. Eight uniform geometries with practical constraints of a limited number of microphones and maximum array size are evaluated over a range of physical metrics. Results show that baffled circular arrays outperform the other geometries in terms of perceptually relevant frequency range, spatial resolution, directivity and robustness. Moreover, a subjective evaluation of microphone arrays and beamformers is conducted with regards to the quality of the target sound, interference suppression and overall quality of simulated music performance recordings. Baffled circular arrays achieve higher target quality and interference suppression than alternative geometries with wideband signals. Furthermore, subjective scores of beamformers regarding target quality and interference suppression agree well with beamformer onaxis and off-axis responses; with wideband signals the superdirective beamformer achieves the highest overall quality.