Dynamic blind source separation based on source-direction prediction

Deterministic techniques are based on the source-directions and multipath characteristics of the reverberant environment for different source signals. However, searching for the desired directions of the time-block sequence of an acoustic signal is time consuming, and existing deterministic methods rarely consider the motion properties of the acoustic source. In this paper, a dynamic source-direction prediction method for real-time blind convolutive mixtures based on a Kalman filter is proposed. First, the convolutive mixture signals captured by the coincident array geometry are formulated, and the relationship between source-direction and source separation is developed. Second, motion prediction based on a Kalman filter is theoretically analyzed, and the motion of a source is modeled as a noise-driven position integrator with enough samples. Then, a dynamic source-direction prediction method for real-time blind source separation based on a Kalman filter is proposed to predict the directions of a time sequential signal. Combined with the local direction searching method, our proposed method has a self-correction ability according to the three-sigma rule. Finally, extensive experiments are performed with three-source convolutive mixtures of speeches in English and Chinese, whose direction varies in linear and nonlinear motions. The signal-to-distortion and signal-to-interference of the separated signals are calculated, and the experimental results demonstrate the feasibility and validity of the proposed method. We formulate the convolutive mixture signals captured by the coincident array geometry.We propose a dynamic source-direction prediction method for real-time blind source separation based on a Kalman filter.We propose a self-correction ability for source-direction prediction.Convolutive mixtures of speeches in English and Chinese, whose direction varies in linear and nonlinear motions, have been separated.The signal-to-distortion and signal-to-interference of the separated signals are calculated to demonstrate its correctness.

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