LOW COMPLEXITY SPEAKER VERIFICATION USING SIMPLIFIED HIDDEN MARKOV MODELS WITH UNIVERSAL COHORT MODELS AND AUTOMATIC SCORE THRESHOLDING

A low complexity speaker verification system that employs universal cohort models an automatic score thresholding. The universal cohort models are generated using a simplified cohort model generating scheme. In certain embodiments of the invention, a simplified hidden Markov modeling (HMM) scheme is used to generate the cohort models. In addition, the low complexity speaker verification system is trained by various users of the low complexity speaker verification system. The total number of users of the low complexity speaker verification system may be modified over time as required by the specific application, and the universal cohort models may be updated accordingly to accommodate the new users. The present invention employs a combination of universal cohort modeling and thresholding to ensure high performance. In addition, given the simplified generation of the cohort models and training of the low complexity speaker verification system, substantially reduced processing resources and memory are amenable for high performance of the low complexity speaker verification system. In certain embodiments of the invention, the invention is an integrated speaker training and speaker verification system that performs both training and speaker verification.