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识别不熟悉的声音:考察样本时长和列队大小的系统变量。

Identifying unfamiliar voices: Examining the system variables of sample duration and parade size.

机构信息

Nottingham Trent University, Nottingham, UK.

University of Cambridge, Cambridge, UK.

出版信息

Q J Exp Psychol (Hove). 2023 Dec;76(12):2804-2822. doi: 10.1177/17470218231155738. Epub 2023 Mar 7.

DOI:10.1177/17470218231155738
PMID:36718784
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10655699/
Abstract

Voice identification parades can be unreliable due to the error-prone nature of earwitness responses. UK government guidelines recommend that voice parades should have nine voices, each played for 60 s. This makes parades resource-consuming to construct. In this article, we conducted two experiments to see if voice parade procedures could be simplified. In Experiment 1 ( = 271, 135 female), we investigated if reducing the duration of the voice samples on a nine-voice parade would negatively affect identification performance using both conventional logistic and signal detection approaches. In Experiment 2 ( = 270, 136 female), we first explored if the same sample duration conditions used in Experiment 1 would lead to different outcomes if we reduced the parade size to include only six voices. Following this, we pooled the data from both experiments to investigate the influence of target-position effects. The results show that 15-s sample durations result in statistically equivalent voice identification performance to the longer 60-s sample durations, but that the 30-s sample duration suffers in terms of overall signal sensitivity. This pattern of results was replicated using both a nine- and a six-voice parade. Performance on target-absent parades were at chance levels in both parade sizes, and response criteria were mostly liberal. In addition, unwanted position effects were present. The results provide initial evidence that the sample duration used in a voice parade may be reduced, but we argue that the guidelines recommending a parade with nine voices should be maintained to provide additional protection for a potentially innocent suspect given the low target-absent accuracy.

摘要

由于耳证人反应的易错性,语音识别列队可能不可靠。英国政府指南建议,语音列队应由九个声音组成,每个声音播放 60 秒。这使得列队的构建需要大量资源。在本文中,我们进行了两项实验,以确定是否可以简化语音列队程序。在实验 1(n=271,女性 135 人)中,我们使用传统逻辑和信号检测方法,研究了减少九人列队中语音样本的持续时间是否会对识别性能产生负面影响。在实验 2(n=270,女性 136 人)中,我们首先探讨了在实验 1 中使用相同的样本持续时间条件,如果我们将列队大小减少到仅包含六个声音,是否会导致不同的结果。在此之后,我们将两个实验的数据合并起来,以研究目标位置效应的影响。结果表明,15 秒的样本持续时间导致的语音识别性能与更长的 60 秒样本持续时间在统计学上等效,但 30 秒的样本持续时间在整体信号灵敏度方面存在劣势。使用九人和六声音列队都复制了这种结果模式。在两个列队大小中,目标不存在的列队的表现都处于随机水平,响应标准大多宽松。此外,还存在不需要的位置效应。这些结果初步证明,在语音列队中使用的样本持续时间可以缩短,但我们认为,鉴于目标不存在的准确性较低,建议使用九个声音的列队的指南应得到维持,以对潜在无辜的嫌疑人提供额外的保护。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e997/10655699/7e094c40095c/10.1177_17470218231155738-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e997/10655699/f4be0cccdf9d/10.1177_17470218231155738-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e997/10655699/e0d6015c7e35/10.1177_17470218231155738-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e997/10655699/486181d1b302/10.1177_17470218231155738-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e997/10655699/444482a93a51/10.1177_17470218231155738-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e997/10655699/7e094c40095c/10.1177_17470218231155738-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e997/10655699/f4be0cccdf9d/10.1177_17470218231155738-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e997/10655699/e0d6015c7e35/10.1177_17470218231155738-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e997/10655699/486181d1b302/10.1177_17470218231155738-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e997/10655699/444482a93a51/10.1177_17470218231155738-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e997/10655699/7e094c40095c/10.1177_17470218231155738-fig5.jpg

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本文引用的文献

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Evaluating earwitness identification procedures: adapting pre-parade instructions and parade procedure.评估耳证人辨认程序:调整列队前指示和列队程序。
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2
Line-Up Image Position in Simultaneous and Sequential Line-Ups: The Effects of Age and Viewing Distance on Selection Patterns.同步和顺序列队中列队图像位置:年龄和观看距离对选择模式的影响。
Front Psychol. 2020 Jul 1;11:1349. doi: 10.3389/fpsyg.2020.01349. eCollection 2020.
3
Estimating the proportion of guilty suspects and posterior probability of guilt in lineups using signal-detection models.
使用信号检测模型估计列队辨认中有罪嫌疑人的比例和有罪的后验概率。
Cogn Res Princ Implic. 2020 May 13;5(1):21. doi: 10.1186/s41235-020-00219-4.
4
A method for calculating the strength of evidence associated with an earwitness's claimed recognition of a familiar speaker.一种用于计算与耳证人声称识别出熟悉说话者相关的证据强度的方法。
Sci Justice. 2019 Nov;59(6):585-596. doi: 10.1016/j.scijus.2019.07.001. Epub 2019 Jul 9.
5
Voice parade procedures: optimising witness performance.嗓音障碍评估程序:证人表现的最优化。
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Acoustic voice variation within and between speakers.说话人内和说话人间的声学嗓音变化。
J Acoust Soc Am. 2019 Sep;146(3):1568. doi: 10.1121/1.5125134.
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Designing police lineups to maximize memory performance.设计警察列队以最大限度地提高记忆表现。
J Exp Psychol Appl. 2019 Sep;25(3):410-430. doi: 10.1037/xap0000222. Epub 2019 May 16.
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Gorilla in our midst: An online behavioral experiment builder.潜伏在我们中间的大猩猩:一个在线行为实验构建器。
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