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We address the problem of online localization and tracking of multiple movingspeakers in reverberant environments. The paper has the followingcontributions. We use the direct-path relative transfer function (DP-RTF), aninter-channel feature that encodes acoustic information robust againstreverberation, and we propose an online algorithm well suited for estimatingDP-RTFs associated with moving audio sources. Another crucial ingredient of theproposed method is its ability to properly assign DP-RTFs to audio-sourcedirections. Towards this goal, we adopt a maximum-likelihood formulation and wepropose to use an exponentiated gradient (EG) to efficiently updatesource-direction estimates starting from their currently available values. Theproblem of multiple speaker tracking is computationally intractable because thenumber of possible associations between observed source directions and physicalspeakers grows exponentially with time. We adopt a Bayesian framework and wepropose a variational approximation of the posterior filtering distributionassociated with multiple speaker tracking, as well as an efficient variationalexpectation-maximization (VEM) solver. The proposed online localization andtracking method is thoroughly evaluated using two datasets that containrecordings performed in real environments.

Online Localization and Tracking of Multiple Moving Speakers in Reverberant Environments