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多模态身份信息并不能提高面部和语音身份匹配的准确性。

Face and voice identity matching accuracy is not improved by multimodal identity information.

作者信息

Smith Harriet M J, Ritchie Kay L, Baguley Thom S, Lavan Nadine

机构信息

NTU Psychology, Nottingham Trent University, Nottingham, UK.

School of Psychology, University of Lincoln, Lincoln, UK.

出版信息

Br J Psychol. 2025 May;116(2):367-385. doi: 10.1111/bjop.12757. Epub 2024 Dec 17.

Abstract

Identity verification from both faces and voices can be error-prone. Previous research has shown that faces and voices signal concordant information and cross-modal unfamiliar face-to-voice matching is possible, albeit often with low accuracy. In the current study, we ask whether performance on a face or voice identity matching task can be improved by using multimodal stimuli which add a second modality (voice or face). We find that overall accuracy is higher for face matching than for voice matching. However, contrary to predictions, presenting one unimodal and one multimodal stimulus within a matching task did not improve face or voice matching compared to presenting two unimodal stimuli. Additionally, we find that presenting two multimodal stimuli does not improve accuracy compared to presenting two unimodal face stimuli. Thus, multimodal information does not improve accuracy. However, intriguingly, we find that cross-modal face-voice matching accuracy predicts voice matching accuracy but not face matching accuracy. This suggests cross-modal information can nonetheless play a role in identity matching, and face and voice information combine to inform matching decisions. We discuss our findings in light of current models of person perception, and consider the implications for identity verification in security and forensic settings.

摘要

来自面部和声音的身份验证都可能容易出错。先前的研究表明,面部和声音传达着一致的信息,跨模态的陌生面孔与声音匹配是可能的,尽管准确率通常较低。在当前的研究中,我们探讨了使用添加了第二种模态(声音或面部)的多模态刺激,是否能够提高面部或声音身份匹配任务的表现。我们发现,面部匹配的总体准确率高于声音匹配。然而,与预测相反的是,在匹配任务中呈现一个单模态刺激和一个多模态刺激,与呈现两个单模态刺激相比,并没有提高面部或声音匹配的准确率。此外,我们发现,与呈现两个单模态面部刺激相比,呈现两个多模态刺激并没有提高准确率。因此,多模态信息并不能提高准确率。然而,有趣的是,我们发现跨模态的面孔-声音匹配准确率能够预测声音匹配准确率,但不能预测面部匹配准确率。这表明跨模态信息在身份匹配中仍然可以发挥作用,并且面部和声音信息结合起来为匹配决策提供依据。我们根据当前的人物感知模型讨论了我们的研究结果,并考虑了其在安全和法医环境中身份验证方面的意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a512/11984343/2eaf696d3610/BJOP-116-367-g002.jpg

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