Score normalization for text-independent speaker verification systems

This paper discusses several aspects of score normalization for text-independent speaker verification. The theory of score normalization is explained using Bayes' theorem and detection error trade-off plots. Based on the theory, the world, cohort, and zero normalization techniques are explained. A novel normalization technique, test normalization, is introduced. Experiments showed significant improvements for this new technique compared to the standard techniques. Finally, there is a discussion of the use of additional knowledge to further improve the normalization methods. Here, the test normalization method is extended to use knowledge of the handset type, (C) 2000 Academic Press.