Kamiloğlu Roza G, Boateng George, Balabanova Alisa, Cao Chuting, Sauter Disa A
Department of Psychology, University of Amsterdam, REC G, Nieuwe Achtergracht 129 B, PO Box 15900, 1001 NK Amsterdam, The Netherlands.
Department of Management, Technology, and Economics, ETH Zürich, Zurich, Switzerland.
J Nonverbal Behav. 2021;45(4):419-454. doi: 10.1007/s10919-021-00375-1. Epub 2021 Jul 24.
The human voice communicates emotion through two different types of vocalizations: nonverbal vocalizations (brief non-linguistic sounds like laughs) and speech prosody (tone of voice). Research examining recognizability of emotions from the voice has mostly focused on either nonverbal vocalizations or speech prosody, and included few categories of positive emotions. In two preregistered experiments, we compare human listeners' (total = 400) recognition performance for 22 positive emotions from nonverbal vocalizations ( = 880) to that from speech prosody ( = 880). The results show that listeners were more accurate in recognizing most positive emotions from nonverbal vocalizations compared to prosodic expressions. Furthermore, acoustic classification experiments with machine learning models demonstrated that positive emotions are expressed with more distinctive acoustic patterns for nonverbal vocalizations as compared to speech prosody. Overall, the results suggest that vocal expressions of positive emotions are communicated more successfully when expressed as nonverbal vocalizations compared to speech prosody.
The online version contains supplementary material available at 10.1007/s10919-021-00375-1.
人类的声音通过两种不同类型的发声来传达情感:非语言发声(如笑声等简短的非语言声音)和言语韵律(语调)。研究从声音中识别情感的能力大多聚焦于非语言发声或言语韵律,且涉及的积极情感类别较少。在两项预先注册的实验中,我们将人类听众(共400名)对880个非语言发声中的22种积极情感的识别表现与对880个言语韵律中的22种积极情感的识别表现进行了比较。结果表明,与韵律表达相比,听众从非语言发声中识别大多数积极情感时更准确。此外,机器学习模型的声学分类实验表明,与言语韵律相比,非语言发声中积极情感的表达具有更独特的声学模式。总体而言,结果表明,与言语韵律相比,积极情感以非语言发声的形式表达时,其声音表达更为成功。
在线版本包含可在10.1007/s10919-021-00375-1获取的补充材料。