Total: 1
Due to the increasing use of fusion in speaker recognition systems, features that are complementary to MFCCs offer opportunities to advance the state of the art. One promising feature is based on group delay, however this can suffer large variability due to its numerical formulation. In this paper, we investigate reducing this variability in group delay features with least squares regularization. Evaluations on the NIST 2001 and 2008 SRE databases show a relative improvement of at least 6% and 18% EER respectively when group delay-based system is fused with MFCC-based system.