Database selection for forensic voice comparison

Abstract

Defining the relevant population to sample is an important issue in data-based implementation of the likelihood-ratio framework for forensic voice comparison. We present a logical argument that because an investigator or prosecutor only submits suspect and offender recordings for forensic analysis if they sound sufficiently similar to each other, the appropriate defense hypothesis for the forensic scientist to adopt will usually be that the suspect is not the speaker on the offender recording but is a member of a population of speakers who sound sufficiently similar that an investigator or prosecutor would submit recordings of these speakers for forensic analysis. We propose a procedure for selecting background, development, and test databases using a panel of human listeners, and empirically test an automatic procedure inspired by the above. Although the automatic procedure is not entirely consistent with the logical arguments and human-listener procedure, it serves as a proof of concept for the importance of database selection. A forensicvoice- comparison system using the automatic database-selection procedure outperformed systems with random database selection.