Forensic voice comparison – Human-supervised-automatic approach

Geoffrey Stewart Morrison*, Philip Weber, Ewald Enzinger, Beltrán Labrador, Alicia Lozano-Díez, Daniel Ramos, Joaquín González-Rodríguez

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputEntry for encyclopedia/dictionary

Abstract

The human-supervised-automatic analytical approach to forensic voice comparison in conjunction with the likelihood-ratio interpretive framework is described. Practitioner tasks are described, including adoption of relevant hypotheses for the case, assessment of the conditions of the questioned-speaker and known-speaker recordings in the case, and selection of data representing the relevant population and reflecting the conditions for the case. Software tools are also described. An example is provided of a forensic-voice-comparison system based on state-of-the-art automatic-speaker-recognition technology. Also described are the calibration and validation of that system using a benchmark dataset reflecting the conditions of a real forensic case.
Original languageEnglish
Title of host publicationEncyclopedia of Forensic Sciences
EditorsM Houck, H Eldridge, S Lewis, K Lothridge, P Reedy, L Wilson
PublisherElsevier
Chapter00182
Pages720-736
Number of pages17
Volume2
Edition3
ISBN (Print)9780128236772
DOIs
Publication statusPublished - 1 Nov 2022

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