Technical forensic speaker recognition: Evaluation, types and testing of evidence
Date
2006
Authors
Rose, Philip
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Publisher
Elsevier
Abstract
Important aspects of Technical Forensic Speaker Recognition, particularly those associated with evidence, are exemplified and critically discussed, and comparisons drawn with generic Speaker Recognition. The centrality of the Likelihood Ratio of Bayes' theorem in correctly evaluating strength of forensic speech evidence is emphasised, as well as the many problems involved in its accurate estimation. It is pointed out that many different types of evidence are of use, both experimentally and forensically, in discriminating same-speaker from different-speaker speech samples, and some examples are given from real forensic case-work to illustrate the Likelihood Ratio-based approach. The extent to which Technical Forensic Speaker Recognition meets the Daubert requirement of testability is also discussed.
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Keywords
Keywords: Evaluation; Maximum likelihood estimation; Pattern recognition systems; Theorem proving; Forensic speech; Likelihood ratio; Speaker recognition; Speech recognition
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Source
Computer Speech and Language
Type
Journal article
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Restricted until
2037-12-31
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