Elements of information theory
Elements of information theory
A tutorial on text-independent speaker verification
EURASIP Journal on Applied Signal Processing
Target dependent score normalization techniques and their application to signature verification
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
An overview of text-independent speaker recognition: From features to supervectors
Speech Communication
Adaptive client-impostor centric score normalization: a case study in fingerprint verification
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Pattern Recognition Letters
Speaker verification score normalization using speaker model clusters
Speech Communication
Is masking a relevant aspect lacking in MFCC? A speaker verification perspective
Pattern Recognition Letters
Hi-index | 0.10 |
A novel score normalization scheme for speaker verification is presented. The proposed technique is based on the widely used test-normalization method (Tnorm), which compensates test-dependent variability using a fixed cohort of impostors. The new procedure selects a speaker-dependent subset of impostor models from the fixed cohort using a distance-based criterion. Selection of the sub-cohort is made using a distance measure based on a fast approximation of the Kullback-Leibler (KL) divergence for Gaussian mixture models (GMM). The proposed technique has been called KL-Tnorm, and outperforms Tnorm in computational efficiency. Experimental results using NIST 2005 Speaker Recognition Evaluation protocol also show a stable performance improvement of our method on standard speaker recognition systems.