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Speaker verification with multiple classifier fusion using Bayes based confidence measure

A novel framework based on Bayes-based confidence measure (BBCM) for Multiple Classifier System (MCS) fusion is proposed. As shown here, BBCM based MCS combination scheme corresponds to the ordinary Bayes fusion weighted by the reliability of each individual classifier. BBCM provides a formal model for heuristic weighting functions employed elsewhere. When compared with the ordinary Bayesian fusion, the proposed method leads to reductions as high as 20% and 50% in EER and the area below the ROC curve, respectively, in speaker verification.