The relevant population in forensic voice comparison: Effects of varying delimitations of social class and age

Abstract

In forensic voice comparison, the expert is typically instructed to compare the voices in a pair of offender and suspect samples. To appropriately evaluate the strength of such evidence, it is necessary to consider both the similarity between the samples and their typicality in the wider, relevant population. This paper considers the effects of different definitions of the relevant population when computing numerical likelihood ratios (LR), with specific regard to socio-economic class and age. Input data consist of cubic polynomial estimations of F1, F2 and F3 trajectories for /eɪ/ in New Zealand English. Calibrated LRs are computed for a sociolinguistically homogeneous sets of test data using three systems comprising of training and reference data which, with regard to the social class or age of the test speakers, are Matched, Mismatched or Mixed. The distributions of LRs were found to be relatively stable across systems, although LRs for individual comparisons may be substantially affected. As expected, the Mismatched systems produced the worst validity, while the Matched systems produced the best validity. The implications of these results for voice comparison casework are considered in light of the paradox that one cannot know for certain the sociolinguistic community to which the offender belongs.