Abstract
On the one hand, commercial biometric systems and forensic identification require different approaches in order to evaluate system outputs. On the other hand, bayesian approach for evidence analysis and forensic reporting perfectly suits the needs of the court and the forensic scientist. Inside this bayesian framework, any biometric system can be adapted to provide its results in the form of likelihood ratios (LR) (being so converted in a forensic identification system), and performance of the forensic system can be then assessed according to the bayesian approach. We will focus on a specific biometric characteristic, showing how forensic speaker recognition can be reported by means of bayesian technique. Results including NIST-Ahumada and providing LR scores in the form of Tippet plots (and compared with DET plots) will be finally presented.
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Gonzalez-Rodriguez, J., Fiérrez-Aguilar, J., Ortega-Garcia, J., Lucena-Molina, J.J. (2002). Biometric Identification in Forensic Cases According to the Bayesian Approach. In: Tistarelli, M., Bigun, J., Jain, A.K. (eds) Biometric Authentication. BioAW 2002. Lecture Notes in Computer Science, vol 2359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47917-1_18
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DOI: https://doi.org/10.1007/3-540-47917-1_18
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