Research into auditory analysis in forensic speaker identification has attracted little attention, yet it is regarded as an essential component of forensic speaker identification. One possible reason for this lack of interest may be associated with the difficulty of knowing how to present the results of auditory analysis in a logical and quantifiable way. The use of likelihood ratios enables these criteria to be met. In this paper, likelihood ratios for four readilyobservable phonetic features of Australian okay are calculated to demonstrate how the Bayesian approach can be applied to auditory data. These features include (1) the reduction of okay to one syllable by deletion of the initial vowel; (2) presence of lip rounding in the initial vowel; (3) palatalisation of the second vowel; and (3) presence of creaky voice.
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