Mapping across feature spaces in forensic voice comparison: the contribution of auditory-based voice quality to (semi-)automatic system testing

In forensic voice comparison, there is increasing focus on the integration of automatic and phonetic methods to improve the validity and reliability of voice evidence to the courts. In line with this, we present a comparison of long-term measures of the speech signal to assess the extent to which they capture complementary speaker-specific information. Likelihood ratio-based testing was conducted using MFCCs and (linear and Mel-weighted) long-term formant distributions (LTFDs). Fusing automatic and semi-automatic systems yielded limited improvement in performance over the baseline MFCC system, indicating that these measures capture essentially the same speaker-specific information. The output from the best performing system was used to evaluate the contribution of auditory-based analysis of supralaryngeal (filter) and laryngeal (source) voice quality in system testing. Results suggest that the problematic speakers for the (semi-)automatic system are, to some extent, predictable from their supralaryngeal voice quality profiles, with the least distinctive speakers producing the weakest evidence and most misclassifications. However, the misclassified pairs were still easily differentiated via auditory analysis. Laryngeal voice quality may thus be useful in resolving problematic pairs for (semi-)automatic systems, potentially improving their overall performance.