Forensic Voice Comparison: Human-Supervised-Automatic Approach

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.