Automatic speaker recognition using dynamic Bayesian network

This paper presents a novel approach to automatic speaker recognition using dynamic Bayesian network (DBN). DBNs have a precise and well-understood probabilistic semantics, and the ability to incorporate prior knowledge, to represent arbitrary non-linearities, and to handle hidden variables and missing data in a principled way with high extensibility. Experimental evaluation over YOHO corpus shows promising results compared to other classical methods.