Background Specificity in Forensic Voice Comparison and Its Relation to the Bayesian Prior Probability

Michael Wagner, Yuko Kinoshita

    Research output: Contribution to conferencePaper

    Abstract

    This study investigates the effect of background data specifici-ty on likelihood ratio and prior odds, and consequently on the posterior odds outcome. It is motivated by discussions on the correct choice of speaker recognition background, particularly in forensic voice comparison. We performed strictly controlled experiments with the ANDOSL database where background specificity is the sole independent variable. Results show that target and non-target scores are better separated with less spe-cific background, but that in turn priors must be adjusted down. Because the risk of class recognition instead of individ-ual recognition increases with lower background specificity, we suggest that the prior probability in the Bayes formula is factorised into one part that remains in the domain of the trier of fact – as is conventional – and another part that is related to the specificity of the assumed or agreed background.
    Original languageEnglish
    Pages353-356
    Publication statusPublished - 2016
    EventSixteenth Australasian International Conference on Speech Science and Technology - Parramatta, Australia
    Duration: 1 Jan 2016 → …

    Conference

    ConferenceSixteenth Australasian International Conference on Speech Science and Technology
    Period1/01/16 → …

    Fingerprint Dive into the research topics of 'Background Specificity in Forensic Voice Comparison and Its Relation to the Bayesian Prior Probability'. Together they form a unique fingerprint.

    Cite this