Mapping 24 Emotions Conveyed by Brief Human Vocalization
Mapping 24 Emotions Conveyed by Brief Human Vocalization
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DOI：
10.1037/amp0000399
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发表时间：
2019-09-01
影响因子：
16.4
通讯作者：
Keltner, Dacher
中科院分区：
文献类型：
--
作者：
Cowen, Alan S.;Elfenbein, Hillary Anger;Keltner, Dacher
情感发声是人类社会生活的核心。最近的研究表明，人们在简短的发声中至少能识别出13种情绪。这种能力在发展的早期就出现了，在不同的文化中以某种形式保存下来，并告知人们对音乐的情感反应。人们对发声中的情感识别是如何在我们所说的语义空间中构建的还知之甚少，对语义空间的研究解决了该领域的关键问题：有多少种不同的情感可以表达？表情是否传达情感类别或情感评价（例如，效价，觉醒）？情绪表达的识别是离散的还是连续的？在情绪分类学新理论方法的指导下，我们应用大规模数据收集和分析技术，对美国英语使用者（N = 1，105）在实验室环境（研究1）中产生的2，032个情绪语音爆发和在真实的世界（研究2）中发现的48个情绪语音爆发进行判断。我们发现，声音爆发传达至少24种不同的情感。同情（Symptom）。敬畏），比情感评价（包括效价和唤醒）更能组织情感识别。与离散情感理论相反，爆发声传达的情感类别通过具有连续变化含义的平滑梯度来桥接。我们可视化的复杂，高维空间的情感传达简短的人类发声在一个在线的互动地图。
Emotional vocalizations are central to human social life. Recent studies have documented that people recognize at least 13 emotions in brief vocalizations. This capacity emerges early in development, is preserved in some form across cultures, and informs how people respond emotionally to music. What is poorly understood is how emotion recognition from vocalization is structured within what we call a semantic space, the study of which addresses questions critical to the field: How many distinct kinds of emotions can be expressed? Do expressions convey emotion categories or affective appraisals (e.g., valence, arousal)? Is the recognition of emotion expressions discrete or continuous? Guided by a new theoretical approach to emotion taxonomies, we apply large-scale data collection and analysis techniques to judgments of 2,032 emotional vocal bursts produced in laboratory settings (Study 1) and 48 found in the real world (Study 2) by U.S. English speakers (N = 1,105). We find that vocal bursts convey at least 24 distinct kinds of emotion. Emotion categories (sympathy. awe), more so than affective appraisals (including valence and arousal), organize emotion recognition. In contrast to discrete emotion theories, the emotion categories conveyed by vocal bursts are bridged by smooth gradients with continuously varying meaning. We visualize the complex, high-dimensional space of emotion conveyed by brief human vocalization within an online interactive map.