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Recently, Constant Separating Vector (CSV) mixing model has been proposed forthe Blind Source Extraction (BSE) of moving sources. In this paper, weexperimentally verify the applicability of CSV in the blind extraction of amoving speaker and propose a new BSE method derived by modifying the auxiliaryfunction-based algorithm for Independent Vector Analysis. Also, a pilotedvariant is proposed for the method with partially controllable globalconvergence. The methods are verified under reverberant and noisy conditionsusing {\color{red} simulated as well as real-world acoustic conditions}. Theyare also verified within the CHiME-4 speech separation and recognitionchallenge. The experiments corroborate the applicability of CSV as well as theimproved convergence of the proposed algorithms.

Auxiliary Function-Based Algorithm for Blind Extraction of a Moving Speaker