Applying logistic regression to the fusion of the NIST'99 1-speaker submissions

This contribution formulates the decision fusion problem encountered in the design of a multiexpert identity verification system. For this purpose, a Bayesian classifier is used and the influence of the a priori class probabilities is investigated. Logistic regression is introduced as a particular case of the naive Bayesian classifier and is applied to the fusion of all submitted data of the 1-speaker recognition task, part of the NIST'99 campaign.