Forensic voice comparison using likelihood ratios based on polynomial curves fitted to the formant trajectories of Australian English/ai/

Earlier studies have indicated that information regarding speaker identity can be extracted from the dynamic spectral properties of diphthongs. Some studies have conducted likelihood-ratio analyses based on simple models of the dynamic formant properties of diphthongs (e.g., dual-target model), and others have used more sophisticated polynomial curve fitting models but have not conducted likelihood-ratio analyses. The present study examines the strength of evidence which can be produced by a likelihood-ratio analysis based on the coefficients of polynomial curves fitted to the formant trajectories of Australian English /ai/ tokens. A cubic polynomial model offers a substantial improvement over the dual-target model.