Speaker identification in courtroom contexts – Part II: Investigation of bias in individual listeners’ responses

Abstract

In “Speaker identification in courtroom contexts – Part I” individual listeners made speaker-identification judgements on pairs of recordings which reflected the conditions of the questioned-speaker and known-speaker recordings in a real case. The recording conditions were poor, and there was a mismatch between the questioned-speaker condition and the known-speaker condition. No contextual information that could potentially bias listeners’ responses was included in the experiment condition – it was decontextualized with respect to case circumstances and with respect to other evidence that could be presented in the context of a case. Listeners’ responses exhibited a bias in favour of the different-speaker hypothesis. It was hypothesized that the bias was due to the poor and mismatched recording conditions. The present research compares speaker-identification performance between: (1) listeners under the original Part I experiment condition, (2) listeners who were informed ahead of time that the recording conditions would make the recordings sound more different from one another than had they both been high-quality recordings, and (3) listeners who were presented with high-quality versions of the recordings. Under all experiment conditions, there was a substantial bias in favour of the different-speaker hypothesis. The bias in favour of the different-speaker hypothesis therefore appears not to be due to the poor and mismatched recording conditions.

Publication DOI: https://doi.org/10.1016/j.forsciint.2023.111768
Divisions: ?? 50811700Jl ??
College of Engineering & Physical Sciences
College of Business and Social Sciences > Aston Institute for Forensic Linguistics
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Applied AI & Robotics
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies
College of Engineering & Physical Sciences > Aston Centre for Artifical Intelligence Research and Application
Additional Information: 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. Publisher Copyright: Copyright © 2023 The Author(s). Published by Elsevier B.V. This article is licensed under a Creative commons Attribution 4.0 International (CC BY 4.0)
Uncontrolled Keywords: Bias,Forensic voice comparison,Likelihood ratio,Recording condition,Speaker identification
Publication ISSN: 0379-0738
Last Modified: 16 May 2024 07:25
Date Deposited: 22 Jun 2023 15:29
Full Text Link:
Related URLs: https://www.sci ... 379073823002189 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2023-08
Published Online Date: 2023-06-22
Accepted Date: 2023-06-20
Authors: Basu, Nabanita
Weber, Philip (ORCID Profile 0000-0002-3121-9625)
Bali, Agnes S
Rosas-Aguilar, Claudia
Edmond, Gary
Martire, Kristy A
Morrison, Geoffrey Stewart (ORCID Profile 0000-0001-8608-8207)

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