This paper presents a review of various speaker verification approaches in realistic world, and explore a combinational approach between Gaussian Mixture Model (GMM) and Support Vector Machine (SVM) as well as Gaussian Mixture Model (GMM) and Universal Background Model (UBM).

This paper studies optimal decision rules, including estimators and tests, for weakly identified GMM models. We derive the limit experiment GMM, propose a theoretically?motivated class of priors which give rise to quasi?Bayes rules as limiting case. Together with results in previous literature, this establishes desirable properties approach regardless model identification status, we recommend s...