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Correlating cepstra with formant frequencies: : implications for phonetically-informed forensic voice comparison
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Effects of formant settings and channel mismatch on semi-automatic systems in forensic voice comparison
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Sharing innovative methods, data and knowledge across sociophonetics and forensic speech science
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Investigating the forensic applications of global and local temporal representations of speech for dialect discrimination
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The effect of score sampling on system stability in likelihood ratio based forensic voice comparison
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Forensic voice comparison using long-term acoustic measures of voice quality
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The use of the vocal profile analysis for speaker characterization : methodological proposals
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The individual and the system : Assessing the stability of the output of a semi-automatic forensic voice comparison system
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Abstract:
Semi-automatic systems based on traditional linguistic-phonetic features are increasingly being used for forensic voice comparison (FVC) casework. In this paper, we examine the stability of the output of a semi-automatic system, based on the long-term formant distributions (LTFDs) of F1, F2, and F3, as the channel quality of the input recordings decreases. Cross-validated, calibrated GMM-UBM log likelihood-ratios (LLRs) were computed for 97 Standard Southern British English speakers under four conditions. In each condition the same speech material was used, but the technical properties of the recordings changed (high quality studio recording, landline telephone recording, high bit-rate GSM mobile telephone recording and low bit-rate GSM mobile telephone recording). Equal error rate (EER) and the log LR cost function (Cllr) were compared across conditions. System validity was found to decrease with poorer technical quality, with the largest differences in EER (21.66%) and Cllr (0.46) found between the studio and the low bit-rate GSM conditions. However, importantly, performance for individual speakers was affected differently by channel quality. Speakers that produced stronger evidence overall were found to be more variable. Mean F3 was also found to be a predictor of LLR variability, however no effects were found based on speakers’ voice quality profiles.
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URL: https://eprints.whiterose.ac.uk/132139/ https://eprints.whiterose.ac.uk/132139/1/Hughes_et_al_Interspeech_2018.pdf
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Questions, propositions and assessing different levels of evidence : Forensic voice comparison in practice
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Three steps forward for predictability : Consideration of methodological robustness, indexical and prosodic factors, and replication in the laboratory
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WikiDialects: a resource for assessing typicality in forensic voice comparison ...
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What is the relevant population? Considerations for the computation of likelihood ratios in forensic voice comparison
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Mapping across feature spaces in forensic voice comparison: the contribution of auditory-based voice quality to (semi-)automatic system testing
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Perceptual similarity of identical twins across different L1 listeners: the importance of voice quality in Forensic Phonetics ...
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Formant dynamics and durations of um improve the performance of automatic speaker recognition systems
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The relevant population in forensic voice comparison: Effects of varying delimitations of social class and age
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In: Speech Communication 66 (2015), 218-230
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IDS Bibliografie zur Gesprächsforschung
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Front-end approaches to the issue of correlations in forensic speaker comparison
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Front-end approaches to the issue of correlations in forensic speaker comparison
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The definition of the relevant population and the collection of data for likelihood ratio-based forensic voice comparison
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Issues and opportunities: The application of the numerical likelihood ratio framework to forensic speaker comparison
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