Investigators: Erica Gold and Vincent Hughes
Affiliation: Department of Language and Linguistic Science, The University of York



Building on a pilot study carried out by the applicants (Gold and Hughes 2012), the project sets out to investigate two aspects of correlation between speech parameters. The first involves empirical testing of data from a homogeneous group of speakers (DyViS: Nolan 2009) to reveal correlations that may exist between traditional acoustic-phonetic parameters commonly used in forensic speaker comparisons. Secondly, we aim to address theoretical issues underlying the application of logistic regression fusion (Brümmer et al 2007) in a likelihood ratio (LR) framework, by comparing the levels of correlations found in the data against the levels of correlations found for LRs computed by a given system. The results have two sets of implications. Firstly, the results will provide an empirically-based starting point for making informed decisions concerned with the combination of parameters in real forensic speaker comparisons. This applies both to experts working in a LR framework who must account for naïve Bayes, as well as those working in other frameworks where the expert personally selects parameters to consider and combine in casework. Those making uninformed assumptions in regards to correlations that may exist between parameters used in casework could potentially carry out analyses which lead to miscarriages of justice in the representation of the strength of evidence. Secondly, the results are relevant in addressing how appropriate fusion is as a method for combining dependent parameters using LRs. For those working within a LR framework, the results are intended to provide a basis for the development of a Bayesian network (Taroni et al 2006) to create a ‘front-end’ mathematical model of interdependencies between speech parameters in order to appropriately combine parameters.