Speaker: Daniel Ramos.
Abstract: The use of automatic speaker recognition systems in forensic science has undergone a dramatic improvement in recent years in terms of scientific rigor, objectivity, and consensus. As a result, the discipline has become strongly aligned with the recommendations of the recently released ISO 21043 standard for forensic sciences. In this talk, we will identify three elements that are now essential for the proper and standardized use of automatic speaker recognition systems in forensic science. First, the adoption of a Bayesian decision-theoretical framework ensures the logical incorporation of system information, expressed as a likelihood ratio, into the decision-making process of judges or juries. Second, the probabilistic calibration of likelihood ratios ensures that decisions are made optimally by the fact finder. Third, the strict and systematic validation of systems under case-specific conditions ensures that forensic casework is conducted with sufficient quality. In this context, the contribution and impact of the speaker recognition community have been paramount, with the proposal of techniques such as score-based likelihood ratios, proper scoring rules for validation, and probabilistic calibration. These methods have since been progressively adopted in other areas, including forensic biometrics, forensic chemistry, and forensic DNA profiling, and now extend to an ever-growing range of forensic disciplines.
Keynote speech at Odyssey 2026, June, Lisbon, Portugal. Slides available at: https://odyssey2026.inesc-id.pt/keynote-speakers/