Speech Separation of Multiple Moving Speakers Using Multisensor Multitarget Techniques

The general problem addressed in this paper is that of separating the voices of active moving speakers in the presence of background noise and moderate reverberation level in the acoustic field using a single microphone array. We adapt the multisensor multitarget tracking theory to the context of microphone arrays in order to form receptive beams that lock on each moving speaker on an extended time basis and therefore, achieve voice separation. Our approach: 1) incorporates kinematical information of speakers´ movement by using an interacting multiple model (IMM) estimator per speaker in order to constrain the evolution of direction of arrival (DOA) measurements, which characterize various motions of the speakers, and 2) can directly account for measurement origin uncertainty, i.e., which measurement comes from which speaker, by using the probabilistic-data-association technique in conjunction with the IMM estimator. The effectiveness of the approach is illustrated by an extensive simulation study on tracking the DOAs of two speakers with crossing trajectories and three static speakers having a conversation with partially overlapping speech and long pauses