What would a comprehensive atlas of human emotions include? For 50 years, scientists have sought to map emotion-related experience, expression, physiology, and recognition in terms of the "basic six"-anger, disgust, fear, happiness, sadness, and surprise. Claims about the relationships between these six emotions and prototypical facial configurations have provided the basis for a long-standing debate over the diagnostic value of expression (for review and latest installment in this debate, see Barrett et al., p. 1). Building on recent empirical findings and methodologies, we offer an alternative conceptual and methodological approach that reveals a richer taxonomy of emotion. Dozens of distinct varieties of emotion are reliably distinguished by language, evoked in distinct circumstances, and perceived in distinct expressions of the face, body, and voice. Traditional models-both the basic six and affective-circumplex model (valence and arousal)-capture a fraction of the systematic variability in emotional response. In contrast, emotion-related responses (e.g., the smile of embarrassment, triumphant postures, sympathetic vocalizations, blends of distinct expressions) can be explained by richer models of emotion. Given these developments, we discuss why tests of a basic-six model of emotion are not tests of the diagnostic value of facial expression more generally. Determining the full extent of what facial expressions can tell us, marginally and in conjunction with other behavioral and contextual cues, will require mapping the high-dimensional, continuous space of facial, bodily, and vocal signals onto richly multifaceted experiences using large-scale statistical modeling and machine-learning methods.

中文翻译：

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映射激情：情感体验和表达的高维分类。

人类情感的综合图谱包括哪些内容？50年来，科学家们一直试图根据“基本六种”——愤怒、厌恶、恐惧、快乐、悲伤和惊讶——来绘制与情绪相关的体验、表达、生理和认知。关于这六种情绪和典型面部构造之间关系的主张为关于表情的诊断价值的长期争论提供了基础（有关该争论的回顾和最新部分，请参见 Barrett 等人，第 1 页）。基于最近的实证研究结果和方法，我们提供了一种替代的概念和方法，揭示了更丰富的情感分类。数十种不同的情感可以通过语言可靠地区分，在不同的环境中引发，并通过面部、身体和声音的不同表达来感知。传统模型——基本六元模型和情感循环模型（效价和唤醒度）——捕捉了情绪反应中系统变异性的一小部分。相比之下，与情绪相关的反应（例如，尴尬的微笑、胜利的姿势、同情的发声、不同表情的混合）可以用更丰富的情绪模型来解释。鉴于这些进展，我们讨论为什么基本六种情绪模型的测试不是更普遍的面部表情诊断价值的测试。要确定面部表情可以告诉我们什么，以及与其他行为和情境线索结合起来，需要使用大规模统计将面部、身体和声音信号的高维、连续空间映射到丰富的多方面体验上。建模和机器学习方法。