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Online Localization of Multiple Moving Speakers in Reverberant Environments

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Abstract

This paper addresses the problem of online multiple moving speakers localization in reverberant environments. The direct-path relative transfer function (DP-RTF), as defined by the ratio between the first taps of the convolutive transfer function (CTF) of two microphones, encodes the inter-channel direct-path information and is thus used as a localization feature being robust against reverberation. The CTF estimation is based on the cross-relation method. In this work, the recursive least-square method is proposed to solve the cross-relation problem, due to its relatively low computational cost and its good convergence rate. The DP-RTF feature estimated at each time-frequency bin is assumed to correspond to a single speaker. A complex Gaussian mixture model is used to assign each observed feature to one among several speakers. The recursive expectation-maximization algorithm is adopted to update online the model parameters. The method is evaluated with a new dataset containing multiple moving speakers, where the ground-truth speaker trajectories are recorded with a motion capture system.
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Dates and versions

hal-01795462 , version 1 (18-05-2018)

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Xiaofei Li, Bastien Mourgue, Laurent Girin, Sharon Gannot, Radu Horaud. Online Localization of Multiple Moving Speakers in Reverberant Environments. SAM 2018 - 10th IEEE Workshop on Sensor Array and Multichannel Signal Processing, Jul 2018, Sheffield, United Kingdom. pp.405-409, ⟨10.1109/SAM.2018.8448423⟩. ⟨hal-01795462⟩
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