TY - JOUR
T1 - Speaker identification in courtroom contexts - Part I: Individual listeners compared to forensic voice comparison based on automatic-speaker-recognition technology
AU - Basu, Nabanita
AU - Bali, Agnes S
AU - Weber, Philip
AU - Rosas-Aguilar, Claudia
AU - Edmond, Gary
AU - Martire, Kristy A
AU - Morrison, Geoffrey Stewart
N1 - © 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license
(http://creativecommons.org/licenses/by/4.0/).
PY - 2022/12
Y1 - 2022/12
N2 - Expert testimony is only admissible in common law if it will potentially assist the trier of fact to make a decision that they would not be able to make unaided. The present paper addresses 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. Listeners listen to and make probabilistic judgements on pairs of recordings reflecting the conditions of the questioned- and known-speaker recordings in an actual case. Reflecting different courtroom contexts, listeners with different language backgrounds are tested: Some are familiar with the language and accent spoken, some are familiar with the language but less familiar with the accent, and others are less familiar with the language. Also reflecting different courtroom contexts: In one condition listeners make judgements based only on listening, and in another condition listeners make judgements based on both listening to the recordings and considering the likelihood-ratio values output by the forensic-voice-comparison system.
AB - Expert testimony is only admissible in common law if it will potentially assist the trier of fact to make a decision that they would not be able to make unaided. The present paper addresses 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. Listeners listen to and make probabilistic judgements on pairs of recordings reflecting the conditions of the questioned- and known-speaker recordings in an actual case. Reflecting different courtroom contexts, listeners with different language backgrounds are tested: Some are familiar with the language and accent spoken, some are familiar with the language but less familiar with the accent, and others are less familiar with the language. Also reflecting different courtroom contexts: In one condition listeners make judgements based only on listening, and in another condition listeners make judgements based on both listening to the recordings and considering the likelihood-ratio values output by the forensic-voice-comparison system.
KW - x-vector
KW - Forensic voice comparison
KW - Likelihood ratio
KW - Validation
KW - Admissibility
KW - Speaker identification
UR - https://www.sciencedirect.com/science/article/pii/S0379073822003292?via%3Dihub
U2 - 10.1016/j.forsciint.2022.111499
DO - 10.1016/j.forsciint.2022.111499
M3 - Article
C2 - 36283276
SN - 1872-6283
VL - 341
JO - Forensic science international
JF - Forensic science international
M1 - 111499
ER -