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A single experiment is reported that investigated implicit learning using a conjunctive rule set applied to natural words. Participants memorized a training list consisting of words that were either rare-concrete and common-abstract or common-concrete and rare-abstract. At test, they were told of the rule set, but not told what it was. Instead, they were(More)
Biometric iris recognition systems are widely used for a range of identity recognition applications and have been shown to perform with high accuracy. For large-scale deployments, however, system enhancements leading to a reduction in error rates are continually sought. In this paper we investigate the performance of human verification of iris images and(More)
Two experiments are presented to explore the limits when matching a sample to a suspect utilising the hand as a novel biometric. The results of Experiment 1 revealed that novice participants were able to match hands at above-chance levels as viewpoint changed. Notably, a moderate change in viewpoint had no notable effect, but a more substantial change in(More)
This paper presents a new approach to user identity currently being explored within the SuperIdentity project and outlines the specific role that biometric measurements can contribute towards a modelling process. The SuperIdentity project aims to define a novel holistic model wherein the proven strengths of relationships between facets of identity are(More)
We report 4 experiments investigating auditory hindsight bias-the tendency to overestimate the intelligibility of distorted auditory stimuli after learning their identity. An associative priming manipulation was used to vary the amount of processing fluency independently of prior target knowledge. For hypothetical designs, in which hindsight judgments are(More)
Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning(More)
Recent literature has raised the suggestion that voice recognition runs in parallel to face recognition. As a result, a prediction can be made that voices should prime faces and faces should prime voices. A traditional associative priming paradigm was used in two studies to explore within-modality priming and cross-modality priming. In the within-modality(More)
The results of two experiments are presented in which participants engaged in a face-recognition or a voice-recognition task. The stimuli were face-voice pairs in which the face and voice were co-presented and were either "matched" (same person), "related" (two highly associated people), or "mismatched" (two unrelated people). Analysis in both experiments(More)