Vincent Hughes

Issues and opportunities: The application of the numerical likelihood ratio framework to forensic speaker comparison

Across forensic speech science, the likelihood ratio (LR) is increasingly becoming accepted as the logically and legally correct framework for the expression of expert conclusions. However, there remain a number of theoretical and practical shortcomings in the procedures applied for computing LRs based on speech evidence. In this paper we review how the LR is currently applied to speaker comparison evidence and outline three specific areas which deserve further investigation: namely statistical modelling, issues relating to the relevant population and the combination of LRs from correlated parameters. We then consider future directions for confronting these issues and discuss the implications for forensic comparison evidence more generally.

The relevant population in forensic voice comparison

LRs based on different definitions of the relevant population computed.Relevant population varied according to socio-economic class and age.Strength of evidence affected substantially for individual comparisons.Systems based on narrow, appropriate relevant population produce the best validity.Broad definition of class and age preferable to narrow, inappropriate definition. In forensic voice comparison, the expert is typically instructed to compare the voices in a pair of offender and suspect samples. To appropriately evaluate the strength of such evidence, it is necessary to consider both the similarity between the samples and their typicality in the wider, relevant population. This paper considers the effects of different definitions of the relevant population when computing numerical likelihood ratios (LR), with specific regard to socio-economic class and age. Input data consist of cubic polynomial estimations of F1, F2 and F3 trajectories for /e?/ in New Zealand English. Calibrated LRs are computed for a sociolinguistically homogeneous sets of test data using three systems comprising of training and reference data which, with regard to the social class or age of the test speakers, are Matched, Mismatched or Mixed. The distributions of LRs were found to be relatively stable across systems, although LRs for individual comparisons may be substantially affected. As expected, the Mismatched systems produced the worst validity, while the Matched systems produced the best validity. The implications of these results for voice comparison casework are considered in light of the paradox that one cannot know for certain the sociolinguistic community to which the offender belongs.

Changing Words and Sounds: The Roles of Different Cognitive Units in Sound Change

This study considers the role of different cognitive units in sound change: phonemes, contextual variants and words. We examine /u/-fronting and /j/-dropping in data from three generations of Derby English speakers. We analyze dynamic formant data and auditory judgments, using mixed effects regression methods, including generalized additive mixed models (GAMMs). /u/-fronting is reaching its end-point, showing complex conditioning by context and a frequency effect that weakens over time. /j/-dropping is declining, with low-frequency words showing more innovative variants with /j/ than high-frequency words. The two processes interact: words with variable /j/-dropping (new) exhibit more fronting than words that never have /j/ (noodle) even when the /j/ is deleted. These results support models of change that rely on phonetically detailed representations for both word- and sound-level cognitive units.

Three steps forward for predictability. Consideration of methodological robustness, indexical and prosodic factors, and replication in the laboratory

Abstract There is now abundant evidence that phonetic forms are shaped by probabilistic effects reflecting predictability or informativity. We outline a number of challenges for such work, where theoretical claims are often based on small differences in acoustic measurements, or interpretations of small statistical effect sizes. We outline caveats about the methods and assumptions encountered in many studies of predictability effects, particularly regarding corpus-based approaches. We consider the wide range of factors that influence patterns of variability in phonetic forms, taking a broad perspective on what is meant by “the message” in order to show that predictability effects need to be considered alongside many others, including indexical and prosodic factors. We suggest a number of ways forward to extend our understanding of the form-predictability relationship.

Questions, propositions and assessing different levels of evidence: Forensic voice comparison in practice

This paper contributes to the ongoing discussion about the distinction between observations and propositions in forensic inference, with a specific focus on forensic voice comparison casework conducted in the UK. We outline both linguistic and legal issues which make the evaluation of voice evidence and the refinement of propositions problematic in practice, and illustrate these using case examples. We will argue that group-level observations from the offender sample will always be evidential and that the value of this evidence must be determined by the expert. As such, a proposal is made that experts should, at least conceptually, think of voice evidence as having two levels, both with evidential value: group-level and individual-level. The two rely on different underlying assumptions, and the group-level observations can be used to inform the individual-level propositions. However, for the sake of interpretability, it is probably preferable to present only one combined conclusion to the end user. We also wish to reiterate points made in previous work: in providing conclusions, the forensic expert must acknowledge that the value of the evidence is dependent on a number of assumptions (propositions and background information) and these assumptions must be made clear and explicit to the user.

Sample size and the multivariate kernel density likelihood ratio: How many speakers are enough?

Abstract The likelihood ratio (LR) is now widely accepted as the appropriate framework for evaluating expert evidence. However, an empirical issue in forensic voice comparison is the number of speakers required to generate robust LR output and adequately test system performance. In this study, Monte Carlo simulations were used to synthesise temporal midpoint F1, F2 and F3 values from the hesitation marker um from a set of raw data consisting of 86 male speakers of standard southern British English. Using the multivariate kernel density LR approach, these data were used to investigate: (1) the number of development (training) speakers required for adequate calibration, (2) the number of test speakers needed for robust validity, and (3) the effects of varying the number of reference speakers. The experiments were run over 20 replications to assess the effects of which, as well as how many, speakers are included in each set. Predictably, LR output was most imprecise using small samples. Comparison across the three experiments shows that the greatest variability in LR output was found as a function of the number of development speakers – where stable LR output was only achieved with more than 20 speakers. Thus, it is possible to achieve stable performance with small numbers of test and reference speakers, as long as the system is adequately calibrated. Importantly, however, LRs for individual comparisons may still be substantially affected by the inclusion of additional speakers in each set, even when large samples are used.

Examining correlations between phonetic parameters: Implications for forensic speaker comparison

The research presented in this paper builds upon a previous pilot study (Gold and Hughes 2012). This paper explores the correlation structure of speech parameters from a sociolinguistically homogeneous set of male speakers of Southern Standard British English using a series of segmental, suprasegmental and linguistic parameters. Data was extracted from a subset of speakers from the Dynamic Variability in Speech (DyViS) database (Nolan et al., 2009) and consist of: midpoint F1, F2 & F3 values for /a ɔ u/, midpoint F1, F2 & F3 values hesitation markers UM and UH, dynamic F1, F2 & F3 values for PRICE /aɪ/, long-term formant distributions (LTFD) F1-F4, mean and standard deviation of fundamental frequency (F0), mean articulation rate (AR), voice onset time (VOT) for word-initial /t/ and /k/, and click rate (ingressive velaric stops). The results of the study present a complex correlation structure between linguistic-phonetic variables, and not all correlations are predicted by phonetic theory. The results of the correlations are discussed in relation to implications that exist when combining parameters for forensic speaker comparison casework; specifically, the caution that needs to be yielded by experts in casework to avoid over- or under-estimating the strength of evidence.