Resumen de Voice line-ups: testing aural-perceptual recognition on native speakers of a foreign language
The focal point of this PhD thesis is (foreign/native) speaker perception and recognition. To test such phenomena, jurors from British and Spanish universities were selected to answer ad hoc perception surveys (voice line-ups in three distinct languages: English, Spanish, and Dutch) to unravel the correlations of speaker-specific sociolinguistic factors and acoustic parameters impinging upon success/error rates in identification and discrimination tasks.
To gain a more in-depth understanding of real-life scenarios, the properties of the data are adjusted accordingly (reduced duration of voice samples, semi-spontaneous exchanges), which contrasts with the ideal and controlled conditions hitherto used in experiments of this kind. From a methodological point of view, this is one of the main contributions of this work, besides being one of its challenges, since it aims to prove that differentiating speakers by means of acoustic-phonetic analysis is still plausible despite the limitations of the source material.
It is concluded that language familiarity did not influence the results obtained. However, learned languages exhibit a rather unpredictable behaviour. On the other hand, acoustic-phonetic analyses are proven to yield less error rates than the jurors’ responses gathered through identification tests. Nevertheless, jurors’ scores in discrimination tasks reveal even less false alarms, with the exception of the English voice samples’ analysis (0% error rates).
In light of the above, further research is naturally encouraged to verify such claims. These findings are indeed limited to some extent, given the interdisciplinary nature of speaker recognition due to the presence of uncontrolled co-existing influences such as psychological states, the memory, and environmental factors. Despite the fact that statistical correlations were not as sound as one may expect, this thesis brings us a step closer to better understand the intricacies of real-life forensic voice comparison through the analysis of semi-spontaneous speech, which is arguably harder to analyse than the samples recorded under laboratory conditions.
