Speaker verification using adapted user-dependent multilevel fusion

Authors:
Julian Fierrez-Aguilar;Daniel Garcia-Romero;Javier Ortega-Garcia;Joaquin Gonzalez-Rodriguez
Affiliations:
Biometrics Research Lab./ATVS, Escuela Politecnica Superior, Universidad Autonoma de Madrid, Madrid, Spain;Biometrics Research Lab./ATVS, Escuela Politecnica Superior, Universidad Autonoma de Madrid, Madrid, Spain;Biometrics Research Lab./ATVS, Escuela Politecnica Superior, Universidad Autonoma de Madrid, Madrid, Spain;Biometrics Research Lab./ATVS, Escuela Politecnica Superior, Universidad Autonoma de Madrid, Madrid, Spain
Venue:
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Year:
2005

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Abstract

In this paper we study the application of user-dependent score fusion to multilevel speaker recognition. After reviewing related works in multimodal biometric authentication, a new score fusion technique is described. The method is based on a form of Bayesian adaptation to derive the personalized fusion functions from prior user-independent data. Experimental results are reported using the MIT Lincoln Laboratory's multilevel speaker verification system. It is experimentally shown that the proposed adapted fusion method outperforms both user independent and non-adapted user-dependent fusion approaches.