Microphone multiplexing with diffuse noise model-based principal component analysis

Reducing the total data throughput for microphones arrays is often necessary, especially when using very large arrays. However, what information can be lost depends on the processing task at the decoder level. In this paper, we investigate simple ways of linearly down-mixing the microphone signals into a reduced number of channels, using non-adaptive coefficients derived from a diffuse noise model, based only on the geometry of the array. In source separation experiments, this multiplexing scheme provides no significant loss in quality even with a high reduction in the number of transmission channels, and outperforms a multiplexing scheme with random coefficients. It furthermore introduces some robustness with respect to the microphone gains and angle from the sources.