This paper describes the Nuance–Politecnico di Torino (NPT) speaker recognition system submitted to the NIST SRE12 evaluation campaign. Included are the results of postevaluation tests, focusing on the analysis of the effects of score normalization and condition-dependent calibration. The submitted system combines the results of five acoustic recognizers all based on Gaussian Mixture Models (GMMs). Each system has its own front end, with features differing by their type and dimension. We illustrate the process of development data selection and configuration of state-of-the-art technology, which contributed to obtaining good performance in all the test conditions proposed in this evaluation.