Spatio-Temporal Sampling and Distributed Compression of the Sound Field
We investigate how the sound field induced by an acoustic event evolves over space and time. The characteristics of its bidimensional Fourier spectrum are analyzed and spatio-temporal sampling results using an array of microphones are provided for different scenarios of interest. We then address the distributed compression problem using an information-theoretic point of view. In this context, optimal rate-distortion tradeoffs are derived for two scenarios of interest. A linear network setup is first considered, where a central base station aims at recovering with minimum distortion the signals recorded by an infinite line of microphones. A hearing aid problem is then studied, where two hearing devices exchange data over a rate-constrained wireless link in order to provide spatial noise reduction.