Fusion Of Discriminative And Generative Scoring Criteria In Gmm-Based Speaker Verification

The aim of this paper is to demonstrate the complementarity of different scoring methods used in speaker verification. To show that, we implemented two different scoring methods on top of the joint factor analysis model. The results on the telephone part of the NIST's SRE 2008 core condition show that significant increase in performance can be achieved by fusing likelihood ratio-and support vector machine-based scores.