Human perception and biosignal-based identification of posed and spontaneous smiles
Human perception and biosignal-based identification of posed and spontaneous smiles
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DOI：
10.1371/journal.pone.0226328
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发表时间：
2019-12
期刊：
影响因子：
3.7
通讯作者：
M. Perusquía-Hernández;S. Ayabe‐Kanamura;Kenji Suzuki
中科院分区：
文献类型：
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作者：
M. Perusquía-Hernández;S. Ayabe‐Kanamura;Kenji Suzuki
面部表情是代表情感状态的行为线索。正因为如此，它们是情感自我报告的一个不引人注目的替代品。面部表情的感知识别可以在技术辅助下自动执行。一旦面部表情被识别出来，解释通常就留给了现场专家。然而，面部表情并不总是代表感受到的情感;它们也可以是一种沟通工具。因此，面部表情测量容易产生与自我报告相同的偏差。因此，人类情感的自动测量还应该对面部表情的性质进行推断，而不仅仅是描述面部运动。我们提出了两个实验，旨在评估这种自动推理判断是否可能是有利的。特别是，我们研究了摆姿势和自发的微笑之间的差异。第一个实验的目的是引出两种类型的表达。与其他研究相比，引出的姿势表达的时间动态不受引出指令的限制。肌电图（EMG）被用来自动区分它们。自发的微笑被认为是不同的幅度，发病时间，发病和偏移速度独立的生产者的种族构成的微笑。表情类型与基于EMG的自动检测之间的一致性达到94%的准确率。最后，对人类视频编码者之间的一致性的测量表明，尽管感知标签的一致性相当好，但与推理标签的一致性却很差。第二个实验证实，一个外行的准确性区分从自发的微笑是穷人。因此，自动识别的推理标签将是有益的情感评估和进一步研究这一主题。
Facial expressions are behavioural cues that represent an affective state. Because of this, they are an unobtrusive alternative to affective self-report. The perceptual identification of facial expressions can be performed automatically with technological assistance. Once the facial expressions have been identified, the interpretation is usually left to a field expert. However, facial expressions do not always represent the felt affect; they can also be a communication tool. Therefore, facial expression measurements are prone to the same biases as self-report. Hence, the automatic measurement of human affect should also make inferences on the nature of the facial expressions instead of describing facial movements only. We present two experiments designed to assess whether such automated inferential judgment could be advantageous. In particular, we investigated the differences between posed and spontaneous smiles. The aim of the first experiment was to elicit both types of expressions. In contrast to other studies, the temporal dynamics of the elicited posed expression were not constrained by the eliciting instruction. Electromyography (EMG) was used to automatically discriminate between them. Spontaneous smiles were found to differ from posed smiles in magnitude, onset time, and onset and offset speed independently of the producer’s ethnicity. Agreement between the expression type and EMG-based automatic detection reached 94% accuracy. Finally, measurements of the agreement between human video coders showed that although agreement on perceptual labels is fairly good, the agreement worsens with inferential labels. A second experiment confirmed that a layperson’s accuracy as regards distinguishing posed from spontaneous smiles is poor. Therefore, the automatic identification of inferential labels would be beneficial in terms of affective assessments and further research on this topic.