Bali, Agnes S., Basu, Nabanita, Weber, Philip, Rosas-Aguilar, Claudia, Edmond, Gary, Martire, Kristy A. and Morrison, Geoffrey Stewart (2024). Speaker identification in courtroom contexts – Part III: Groups of collaborating listeners compared to forensic voice comparison based on automatic-speaker-recognition technology. Forensic Science International, 360 ,
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 |
Full Text Link: | |
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 ( 0000-0002-3121-9625) Rosas-Aguilar, Claudia Edmond, Gary Martire, Kristy A. Morrison, Geoffrey Stewart ( 0000-0001-8608-8207) |
Download
Version: Accepted Version
Access Restriction: Restricted to Repository staff only
Version: Published Version
License: Creative Commons Attribution
| Preview