Inter-speaker variability in forensic voice comparison: A preliminary evaluation

In forensic voice comparison, it is strongly recommended to follow Bayesian paradigm. In this paradigm, the strength of the forensic evidence is summarized by a likelihood ratio (LR). The LR magnitude quantifies the strength of the evidence: far from unity for a meaningful LR (a LR which supports strongly one of the hypothesis); close to unity when the evidence is next to useless. Despite this nice theoretical aspect, the LR does not embed the reliability of its estimation process itself. And, in various cases, a lack in reliability inside the estimation process is able to destroy the reliability of the resulting LR. It is particularly true when voice comparison is considered, as Speaker Recognition (SR) systems are outputting a score in all situations regardless of the case specific conditions. Furthermore, SR systems use different normalization steps to see their scores as LR and these normalization steps are clearly a potential source of bias. Consequently, a complete view of reliability should be taken into account for forensic voice comparison. This article focuses on one part of this question, the "speaker factor", the characteristics and the behaviors of the two speakers involved in a voice comparison trial.