Confidence based multiple classifier fusion in speaker verification

Authors:
Fernando Huenupán;Nestor Becerra Yoma;Carlos Molina;Claudio Garretón
Affiliations:
Speech Processing and Transmission Laboratory, Department of Electrical Engineering, Universidad de Chile, Santiago, Chile;Speech Processing and Transmission Laboratory, Department of Electrical Engineering, Universidad de Chile, Santiago, Chile;Speech Processing and Transmission Laboratory, Department of Electrical Engineering, Universidad de Chile, Santiago, Chile;Speech Processing and Transmission Laboratory, Department of Electrical Engineering, Universidad de Chile, Santiago, Chile
Venue:
Pattern Recognition Letters
Year:
2008

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Abstract

A novel framework that applies Bayes-based confidence measure for multiple classifier system fusion is proposed. Compared with ordinary Bayesian fusion, the presented approach can lead to reductions as high as 37% and 35% in EER and ROC curve area, respectively, in speaker verification.