Fuzzy estimation of priors in speaker recognition

Abstract

This paper proposes a method to estimate the a priori probability for speakers based on the training data set, speaker models and a fuzzy estimation technique. Speaker identification experiments performed on 138 Gaussian mixture speaker models in the YOHO database using the priors estimated by the fuzzy estimation method showed lower error rates than using those estimated by the probabilistic estimation method.