Comparison of scoring methods used in speaker recognition with Joint Factor Analysis
Ondřej Glembek, Lukáš Burget, Najim Dehak, Niko Brümmer, Patrick J Kenny · 2009
The aim of this paper is to compare different log-likelihood scoring methods, that different sites used in the latest state-of-the-art Joint Factor Analysis (JFA) Speaker Recognition systems. The algorithms use various assumptions and have been derived from various approximations of the objective functions of JFA. We compare the techniques in terms of speed and performance. We show, that approximations of the true log-likelihood ratio (LLR) may lead to significant speedup without any loss in performance.