  This paper describes the submission to fixed condition of NIST SRE 2016 by
Sharif University of Technology (SUT) team. We provide a full description of
the systems that were included in our submission. We start with an overview of
the datasets that were used for training and development. It is followed by
describing front-ends which contain different VAD and feature types. UBM and
i-vector extractor training are the next details in this paper. As one of the
important steps in system preparation, preconditioning the i-vectors are
explained in more details. Then, we describe the classifier and score
normalization methods. And finally, some results on SRE16 evaluation dataset
are reported and analyzed.
