This paper describes the improvement introduced in the Loquendo–Politecnico di Torino (LPT) speaker recognition system submitted to the NIST SRE10 evaluation campaign. This system combines the results of eight core acoustic systems all based on Gaussian Mixture Models (GMMs). We illustrate the key factors, in the selection of the development data and in engineering state-of-the art technology, which contributed to the very good performance and calibration of our system in all the test conditions proposed in this evaluation.