A statistical procedure to adjust for time-interval mismatch in forensic voice comparison


The present paper describes a statistical modeling procedure that was developed to account for the fact that, in a forensic voice comparison analysis conducted for a particular case, there was a long time interval between when the questioned- and known-speaker recordings were made (six years), but in the sample of the relevant population used for training and testing the forensic voice comparison system there was a short interval (hours to days) between when each of multiple recordings of each speaker was made. The present paper also includes results of empirical validation of the procedure. Although based on a particular case, the procedure has potential for wider application given that relatively long time intervals between the recording of questioned and known speakers are not uncommon in casework.

Publication DOI: https://doi.org/10.1016/j.specom.2019.07.001
Divisions: Engineering & Applied Sciences > Computer Science
Engineering & Applied Sciences
Languages & Social Sciences > Aston Institute for Forensic Linguistics
Languages & Social Sciences > English
Languages & Social Sciences
Additional Information: ©2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license.(http://creativecommons.org/licenses/by/4.0/)
Uncontrolled Keywords: Forensic voice comparison,Likelihood ratio,Mismatch,Time interval,Software,Modelling and Simulation,Communication,Language and Linguistics,Linguistics and Language,Computer Vision and Pattern Recognition,Computer Science Applications
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Related URLs: https://www.sci ... sd_search_email (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2019-09-01
Published Online Date: 2019-07-02
Accepted Date: 2019-06-22
Authors: Morrison, Geoffrey Stewart ( 0000-0001-8608-8207)
Kelly, F.



Version: Accepted Version

Access Restriction: Restricted to Repository staff only


Version: Published Version

License: Creative Commons Attribution

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