  This paper addresses the challenge of estimating the relative transfer
function (RTF) vectors of multiple speakers in a noisy and reverberant
environment. More specifically, we consider a scenario where two speakers
activate successively. In this scenario, the RTF vector of the first speaker
can be estimated in a straightforward way and the main challenge lies in
estimating the RTF vector of the second speaker during segments where both
speakers are simultaneously active. To estimate the RTF vector of the second
speaker the so-called blind oblique projection (BOP) method determines the
oblique projection operator that optimally blocks the second speaker. Instead
of blocking the second speaker, in this paper we propose a covariance blocking
and whitening (CBW) method, which first blocks the first speaker and applies
whitening using the estimated noise covariance matrix and then estimates the
RTF vector of the second speaker based on a singular value decomposition. When
using the estimated RTF vectors of both speakers in a linearly constrained
minimum variance beamformer, simulation results using real-world recordings for
multiple speaker positions demonstrate that the proposed CBW method outperforms
the conventional BOP and covariance whitening methods in terms of
signal-to-interferer-and-noise ratio improvement.
