Autonomous signal separation microphone system based on the spatio-temporal gradient analysis

Abstract

This paper presents a novel autonomous directivity microphone system based on the newly proposed spatio-temporal blind source separation. Recently, the methods of blind source separation and multi-deconvolution of source signals have been proposed in various fields, especially, acoustic applications including the cocktail-party problem. The blind source separation principally uses no a priori knowledge about parameters of convolution, filtering and mixing. In the simplest case of the blind source separation problems, observed mixed signals are linear combinations of unknown mutually statistically independent, zero-mean source signals. The spatio-temporal blind signal separation algorithm utilizes the linearity among the four signals: (1) temporal gradient, (2) x; (3) y; and (4) z-directional spatial gradients of the sound-pressure, all of which are governed by the equation of advection. The proposed method, therefore, has an ability to simplify the convolution blind source separation problems into the instantaneous blind source separation over the spatio-temporal gradient space. The acoustical experiments are performed with the particle velocity microphone (Microflown) successfully instead of sound pressure microphones. Because, x; y; and z-directional gradients of the sound pressure are equivalent the temporal derivatives of the corresponding directional particle velocities theoretically.