Speaker identification in courtroom contexts – Part III: Groups of collaborating listeners compared to forensic voice comparison based on automatic-speaker-recognition technology

Abstract

Expert testimony is only admissible in common-law systems if it will potentially assist the trier of fact. In order for a forensic-voice-comparison expert’s testimony to assist a trier of fact, the expert’s forensic voice comparison should be more accurate than the trier of fact’s speaker identification. “Speaker identification in courtroom contexts – Part I” addressed the question of whether speaker identification by an individual lay listener (such as a judge) would be more or less accurate than the output of a forensic-voice-comparison system that is based on state-of-the-art automatic-speaker-recognition technology. The present paper addresses the question of whether speaker identification by a group of collaborating lay listeners (such as a jury) would be more or less accurate than the output of such a forensic-voice-comparison system. As members of collaborating groups, participants listen to pairs of recordings reflecting the conditions of the questioned- and known-speaker recordings in an actual case, confer, and make a probabilistic consensus judgement on each pair of recordings. The present paper also compares group-consensus responses with “wisdom of the crowd” which uses the average of the responses from multiple independent individual listeners.

Publication DOI: https://doi.org/10.1016/j.forsciint.2024.112048
Divisions: ?? 50811700Jl ??
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Applied AI & Robotics
College of Engineering & Physical Sciences
College of Business and Social Sciences > Aston Institute for Forensic Linguistics
Aston University (General)
Funding Information: This research was supported by Research England’s Expanding Excellence in England Fund as part of funding for the Aston Institute for Forensic Linguistics 2019–2024.
Additional Information: Copyright © 2024 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/).
Uncontrolled Keywords: Admissibility,Forensic voice comparison,Likelihood ratio,Speaker identification,Validation
Publication ISSN: 0379-0738
Last Modified: 14 Nov 2024 17:02
Date Deposited: 07 May 2024 11:30
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Related URLs: https://linking ... 379073824001294 (Publisher URL)
PURE Output Type: Article
Published Date: 2024-07
Published Online Date: 2024-05-06
Accepted Date: 2024-05-01
Authors: Bali, Agnes S.
Basu, Nabanita
Weber, Philip (ORCID Profile 0000-0002-3121-9625)
Rosas-Aguilar, Claudia
Edmond, Gary
Martire, Kristy A.
Morrison, Geoffrey Stewart (ORCID Profile 0000-0001-8608-8207)

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