A Comparative Study of Two Statistical Modelling Approaches for Estimating Multivariate Likelihood Ratios in Forensic Voice Comparison

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    The acoustic features used in forensic voice comparison (FVC) are correlated in almost all cases. A sizeable proportion of FVC studies and casework has relied, for statistical modelling, on the multivariate kernel density likelihood ratio (MVKDLR) formula, which considers the correlations between the features and computes an overall combined likelihood ratio (LR) for the offender-suspect comparison. However, following concerns over the robustness of the MVKDLR, in particular its computational weakness and numerical instability specifically when a large number of features are employed, the principal component analysis kernel density likelihood ratio (PCAKDLR) approach was developed as an alternative. In this study, the performance of the two approaches is investigated and compared using Monte Carlo-simulated synthetic data based on the 16th-order Mel Frequency Cepstrum Coefficients extracted from the long vowel /e:/ segments of spontaneous speech uttered by 118 native Japanese male speakers. Performance is assessed in terms of validity (= accuracy) and reliability (= precision), with the log-likelihood ratio cost (Cllr) being used to assess validity and the 95% credible interval (95%CI) to assess reliability
    Original languageEnglish
    Title of host publicationProceedings of the Australasian Language Technology Association Workshop 2017
    Place of PublicationAustralia
    PublisherAustralasian Language Technology Association
    Pages61-69
    Publication statusPublished - 2017
    Event15th Annual Workshop of The Australasian Language Technology Association - Brisbane, Australia, Australia
    Duration: 1 Jan 2017 → …
    https://aclanthology.org/U17-1007/

    Conference

    Conference15th Annual Workshop of The Australasian Language Technology Association
    Country/TerritoryAustralia
    Period1/01/17 → …
    Other6th - 8th December 2017
    Internet address

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