Robust estimation, interpretation and assessment of likelihood ratios in forensic speaker recognition

In this contribution, the Bayesian framework for interpretation of evidence when applied to forensic speaker recognition is introduced. Different aspects of the use of voice as evidence in the court are addressed, as well as the use by the forensic expert of the likelihood ratio as the right way to express the strength of the evidence. Details on computation procedures of likelihood ratios (LR) are given, along with the assessment tools and methods to validate the performance of these Bayesian forensic systems. However, due to the practical scarcity of suspect data and the mismatched conditions between traces and reference populations common in daily casework, Preprint submitted to Computer Speech and Language 26 July 2005 

• Type: Journal
• Year: 2006
• Where: CSL
• Authors: Joaquin Gonzalez-Rodriguez, Andrzej Drygajlo, Daniel Ramos-Castro, Marta Garcia-Gomar, Javier Ortega-Garcia
• Keywords: Automated Reasoning, Bayesian Forensic Systems, CSL 2006, Forensic Speaker Recognition, Likelihood Ratios