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This paper addresses the challenge of estimating the relative transferfunction (RTF) vectors of multiple speakers in a noisy and reverberantenvironment. More specifically, we consider a scenario where two speakersactivate successively. In this scenario, the RTF vector of the first speakercan be estimated in a straightforward way and the main challenge lies inestimating the RTF vector of the second speaker during segments where bothspeakers are simultaneously active. To estimate the RTF vector of the secondspeaker the so-called blind oblique projection (BOP) method determines theoblique projection operator that optimally blocks the second speaker. Insteadof blocking the second speaker, in this paper we propose a covariance blockingand whitening (CBW) method, which first blocks the first speaker and applieswhitening using the estimated noise covariance matrix and then estimates theRTF vector of the second speaker based on a singular value decomposition. Whenusing the estimated RTF vectors of both speakers in a linearly constrainedminimum variance beamformer, simulation results using real-world recordings formultiple speaker positions demonstrate that the proposed CBW method outperformsthe conventional BOP and covariance whitening methods in terms ofsignal-to-interferer-and-noise ratio improvement.

Covariance Blocking and Whitening Method for Successive Relative Transfer Function Vector Estimation in Multi-Speaker Scenarios