The effect of correlation on strength of evidence estimates in Forensic Voice Comparison: Uni-and multivariate Likelihood Ratio-based discrimination with Australian English vowel acoustics

Philip Rose

    Research output: Contribution to journalArticle

    Abstract

    The consequences of ignoring correlations between features in traditional forensic speaker recognition are investigated. Two likelihood ratio-based discrimination experiments on the same multivariate formant data are described, one taking correlation into account and the other not doing so. The discrimination is performed using Naïve Bayes univariate, and multivariate generative Likelihood Ratios (LRs) as discriminant functions, exemplified with Tippett plots and evaluated with the Cllr cost function. It is shown that ignoring within-segment correlation can result in considerable over-or under-estimation of the strength of evidence when traditional features are used, and there is poorer overall discrimination between same-speaker and different-speaker pairs. The use of logistic-regression fusion to handle between-segment correlation is also demonstrated. Copyright
    Original languageEnglish
    Pages (from-to)316-329
    JournalInternational Journal of Biometrics
    Volume2
    Issue number4
    DOIs
    Publication statusPublished - 2010

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