Hierarchical pattern classification for high performance text-independent speaker verification systems

A new algorithm, the hierarchical speaker verification algorithm, is introduced. This algorithm employs a set of unique mapping functions determined from an enrolment utterance that characterize the target voice as a multidimensional martingale random walk process. For sufficiently long verification utterances, the central limit theorem insures that the accumulated scores for the target speaker will be distributed normally about the origin. Impostor speakers, which violate the martingale property, are distributed arbitrarily and widely scattered in the verification space. Excerpts of verification performance experiments are given and extensions to the algorithm for handling noisy channels and speaker template aging are discussed