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 n = 400) recognition performance for 22 positive emotions from nonverbal vocalizations (n = 880) to that from speech prosody (n = 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.

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（简短的非语言声音，如笑声）和语音韵律（语调）。从声音中检测情绪的可识别性的研究主要集中在非语言发声或语音韵律上，并且包括少数类别的积极情绪。在两个预先注册的实验中，我们比较了人类听众（总共n  = 400）对来自非语言发声（n  = 880）和语音韵律（n = 880)。结果表明，与韵律表达相比，听众能更准确地识别来自非语言发声的大多数积极情绪。此外，机器学习模型的声学分类实验表明，与语音韵律相比，非语言发声的积极情绪以更独特的声学模式表达。总体而言，结果表明，与语音韵律相比，当以非语言发声表达时，积极情绪的声音表达更成功地传达。