Tracking Multiple Audio Sources with the von Mises Distribution and Variational EM
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In this paper, we address the problem of simultaneously tracking several audio sources, namely the problem of estimating source trajectories from a sequence of the observed features. We propose to use the von Mises distribution to model audio-source directions of arrival (DOAs) with circular random variables. This leads to a multi-target Kalman filter formulation which is intractable because of the combinatorial explosion of associating observations to state variables over time. We propose a variational approximation of the filter's posterior distribution and we infer a variational expectation maximization (VEM) algorithm which is computationally efficient. We also propose an audio-source birth method that favors smooth source trajectories and which is used both to initialize the number of active sources and to detect new sources. We perform experiments with a recently released dataset comprising several moving sources as well as a moving microphone array.
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