39 results on '"Morrison, Geoffrey Stewart"'
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2. A response to Busey & Klutzke (2022): Regarding subjective assignment of likelihood ratios
3. Speaker identification in courtroom contexts – Part I: Individual listeners compared to forensic voice comparison based on automatic-speaker-recognition technology
4. Validations of an alpha version of the E3 Forensic Speech Science System (E3FS3) core software tools
5. Forensic comparison of fired cartridge cases: Feature-extraction methods for feature-based calculation of likelihood ratios
6. Advancing a paradigm shift in evaluation of forensic evidence: The rise of forensic data science
7. The opacity myth: A response to Swofford & Champod (2022)
8. A strawman with machine learning for a brain: A response to Biedermann (2022) the strange persistence of (source) “identification” claims in forensic literature
9. Consensus on validation of forensic voice comparison
10. Reply to Response to Vacuous standards – Subversion of the OSAC standards-development process
11. Calculation of likelihood ratios for inference of biological sex from human skeletal remains
12. In the context of forensic casework, are there meaningful metrics of the degree of calibration?
13. Vacuous standards – Subversion of the OSAC standards-development process
14. A method for calculating the strength of evidence associated with an earwitness's claimed recognition of a familiar speaker
15. A statistical procedure to adjust for time-interval mismatch in forensic voice comparison
16. Multi-laboratory evaluation of forensic voice comparison systems under conditions reflecting those of a real forensic case (forensic_eval_01) – Conclusion
17. A response to Marquis et al. (2017) What is the error margin of your signature analysis?
18. Avoiding overstating the strength of forensic evidence: Shrunk likelihood ratios/Bayes factors
19. The impact in forensic voice comparison of lack of calibration and of mismatched conditions between the known-speaker recording and the relevant-population sample recordings
20. Score based procedures for the calculation of forensic likelihood ratios – Scores should take account of both similarity and typicality
21. What should a forensic practitioner's likelihood ratio be? II
22. Empirical test of the performance of an acoustic-phonetic approach to forensic voice comparison under conditions similar to those of a real case
23. A comment on the PCAST report: Skip the “match”/“non-match” stage
24. Guest Editor’s note
25. Refining the relevant population in forensic voice comparison – A response to Hicks et alii (2015) The importance of distinguishing information from evidence/observations when formulating propositions
26. Multi-laboratory evaluation of forensic voice comparison systems under conditions reflecting those of a real forensic case ( forensic_eval_01 ) – Introduction
27. Use of relevant data, quantitative measurements, and statistical models to calculate a likelihood ratio for a Chinese forensic voice comparison case involving two sisters
28. What should a forensic practitioner's likelihood ratio be?
29. Special issue on measuring and reporting the precision of forensic likelihood ratios: Introduction to the debate
30. INTERPOL survey of the use of speaker identification by law enforcement agencies
31. A demonstration of the application of the new paradigm for the evaluation of forensic evidence under conditions reflecting those of a real forensic-voice-comparison case
32. Mismatched distances from speakers to telephone in a forensic-voice-comparison case
33. Distinguishing between forensic science and forensic pseudoscience: Testing of validity and reliability, and approaches to forensic voice comparison
34. Likelihood ratio calculation for a disputed-utterance analysis with limited available data
35. Effects of telephone transmission on the performance of formant-trajectory-based forensic voice comparison – Female voices
36. Measuring the validity and reliability of forensic likelihood-ratio systems
37. An empirical estimate of the precision of likelihood ratios from a forensic-voice-comparison system
38. A comparison of procedures for the calculation of forensic likelihood ratios from acoustic–phonetic data: Multivariate kernel density (MVKD) versus Gaussian mixture model–universal background model (GMM–UBM)
39. Forensic voice comparison and the paradigm shift
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