This document briefly describes the systems submitted by the Center for Robust Speech Systems (CRSS) from The University of Texas at Dallas (UTD) in the 2010 NIST Speaker Recognition Evaluation. Our systems primarily use factor analysis as feature extractor [1] and support vector machine (SVM) classification framework. Our main focus in the evaluation is on the telephone trials in the core condition and 10 second train-test condition. Novel elements in our system include a supervised probabilistic principal component analysis (SPPCA) based approach for factor analysis, and an algorithm for optimal selection of the negative samples for training the SVM.