Spatial Upsampling of Sparse Spherical Microphone Array Signals

Abstract

We present a method for spatial upsampling of signals captured with spherical microphone arrays with a limited number of microphones. The upsampling is performed by adding virtual microphone signals using interpolation between the measured array signals. For interpolation, the differences in amplitude and time of neighbored signals are weighted separately. For this, the time differences are determined with a broadband cross-correlation. After the upsampling, the array signals can be represented as spherical harmonics (SH) coefficients at significantly higher orders. This work introduces the proposed upsampling procedure and presents a technical evaluation based on simulated and measured sound fields. Thereby, we focus on the binaural decoding of the upsampled SH signals. For perceptual evaluation, we present the results of a listening experiment evaluating the binaural reproduction of the upsampled signals compared to a baseline Ambisonics decoding and the state-of-the-art decoding with Magnitude Least-Squares optimization. Both the technical and perceptual evaluations consider only array impulse responses, but the algorithm could generally be applied to array streams. The evaluation shows that the proposed method significantly improves the binaural reproduction of low-order spherical microphone array captures compared to established methods.