Processing Pipelines for Efficient, Physically-Accurate Simulation of Microphone Array Signals in Dynamic Sound Scenes

Multichannel acoustic signal processing is predicated on the fact that the interchannel relationships between the received signals can be exploited to infer information about the acoustic scene. Recently there has been increasing interest in algorithms which are applicable in dynamic scenes, where the source(s) and/or microphone array may be moving. Simulating such scenes has particular challenges which are exacerbated when real-time, listener-in-the-loop evaluation of algorithms is required. This paper considers candidate pipelines for simulating the array response to a set of point/image sources in terms of their accuracy, scalability and continuity. A new approach, in which the filter kernels are obtained using principal component analysis from time-aligned impulse responses, is proposed. When the number of filter kernels is ≤40 the new approach achieves more accurate simulation than competing methods.