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慢慢来:在识别微妙的、非刻板的面部表情方面,人类比软件分类器表现更出色。

Gently does it: Humans outperform a software classifier in recognizing subtle, nonstereotypical facial expressions.

作者信息

Yitzhak Neta, Giladi Nir, Gurevich Tanya, Messinger Daniel S, Prince Emily B, Martin Katherine, Aviezer Hillel

机构信息

Department of Psychology, Hebrew University of Jerusalem.

Movement Disorders Unit, Neurological Institute Tel-Aviv Medical Center, Sackler School of Medicine and Sagol School of Neuroscience, Tel-Aviv University.

出版信息

Emotion. 2017 Dec;17(8):1187-1198. doi: 10.1037/emo0000287. Epub 2017 Apr 13.

Abstract

According to dominant theories of affect, humans innately and universally express a set of emotions using specific configurations of prototypical facial activity. Accordingly, thousands of studies have tested emotion recognition using sets of highly intense and stereotypical facial expressions, yet their incidence in real life is virtually unknown. In fact, a commonplace experience is that emotions are expressed in subtle and nonprototypical forms. Such facial expressions are at the focus of the current study. In Experiment 1, we present the development and validation of a novel stimulus set consisting of dynamic and subtle emotional facial displays conveyed without constraining expressers to using prototypical configurations. Although these subtle expressions were more challenging to recognize than prototypical dynamic expressions, they were still well recognized by human raters, and perhaps most importantly, they were rated as more ecological and naturalistic than the prototypical expressions. In Experiment 2, we examined the characteristics of subtle versus prototypical expressions by subjecting them to a software classifier, which used prototypical basic emotion criteria. Although the software was highly successful at classifying prototypical expressions, it performed very poorly at classifying the subtle expressions. Further validation was obtained from human expert face coders: Subtle stimuli did not contain many of the key facial movements present in prototypical expressions. Together, these findings suggest that emotions may be successfully conveyed to human viewers using subtle nonprototypical expressions. Although classic prototypical facial expressions are well recognized, they appear less naturalistic and may not capture the richness of everyday emotional communication. (PsycINFO Database Record

摘要

根据占主导地位的情感理论,人类天生普遍地使用原型面部活动的特定配置来表达一系列情感。因此,数以千计的研究使用高度强烈和刻板的面部表情集来测试情绪识别,但它们在现实生活中的发生率几乎无人知晓。事实上,一个常见的体验是情绪以微妙和非原型的形式表达。这种面部表情是当前研究的重点。在实验1中,我们展示了一种新型刺激集的开发和验证,该刺激集由动态且微妙的情感面部展示组成,在不限制表达者使用原型配置的情况下进行传达。尽管这些微妙表情比原型动态表情更难识别,但人类评分者仍能很好地识别它们,也许最重要的是,他们认为这些表情比原型表情更具生态性和自然主义特征。在实验2中,我们通过将微妙表情和原型表情提交给一个使用原型基本情绪标准的软件分类器,来研究它们的特征。尽管该软件在对原型表情进行分类方面非常成功,但在对微妙表情进行分类时表现很差。从人类专家面部编码员那里获得了进一步的验证:微妙刺激不包含原型表情中存在的许多关键面部动作。总之,这些发现表明,使用微妙的非原型表情可能会成功地将情绪传达给人类观察者。尽管经典的原型面部表情很容易被识别,但它们看起来不那么自然主义,可能无法捕捉日常情感交流的丰富性。(PsycINFO数据库记录)

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