An Issue in the Calculation of Logistic-Regression Calibration and Fusion Weights for Forensic Voice Comparison

Abstract

Logistic regression is a popular procedure for calibration and fusion of likelihood ratios in forensic voice comparison and automatic speaker recognition. The availability of multiple recordings of each speaker in the database used for calculation of calibration/fusion weights allows for different procedures for calculating those weights. Two procedures are compared, one using pooled data and the other using mean values from each speaker-comparison pair. The procedures are tested using an acoustic-phonetic and an automatic forensic-voice¬comparison system. The mean procedure has a tendency to result in better accuracy, but the pooled procedure always results in better precision of the likelihood-ratio output. Index Terms: logistic regression, calibration, fusion, weights, forensic voice comparison, likelihood ratio.