Calibration and Fusion of Parametric and Non-parametric Statistical Methods for Forensic Semi-Automatic Speaker Recognition Systems: experimental results

Abstract

In this paper, the most employed Forensic Semi-Automatic Speaker Recognition (FSASR) approaches used in Italy – as emulated in the IMPAVIDO software, and some variants of them – are investigated from the point of view of the accuracy. In doing this, we employed score calibration and fusion with Logistic Regression (LogReg). The metric used to assess the accuracy was the likelihood-ratio cost (Cllr), while the factors of analysis include the database numerosity, different software implementation of LogReg, and the strategy to consider the features available for the different vowels. Our results show that the LogReg calibration has systematically improved the Cllr, suggesting that also the accuracy of the tested FSASR approaches may be improved introducing calibration. Furthermore, our findings suggest that the tested FSASR approaches give more accurate results when the IMPAVIDO database is used.