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3
Changes in vocal emotion recognition across the life span.生命全程中嗓音情绪识别的变化。
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4
Human emotional vocalizations can develop in the absence of auditory learning.人类情感性发声可以在缺乏听觉学习的情况下发展。
Emotion. 2020 Dec;20(8):1435-1445. doi: 10.1037/emo0000654. Epub 2019 Sep 2.
5
Do facial first impressions reflect a shared social reality?面部第一印象是否反映了共同的社会现实?
Br J Psychol. 2020 May;111(2):215-232. doi: 10.1111/bjop.12390. Epub 2019 Mar 29.
6
Spatial location and emotion modulate voice perception.空间位置和情绪会调节声音感知。
Cogn Emot. 2019 Dec;33(8):1577-1586. doi: 10.1080/02699931.2019.1586647. Epub 2019 Mar 14.
7
The Riddle of Human Emotional Crying: A Challenge for Emotion Researchers.人类情感哭泣之谜:对情感研究者的一项挑战。
Emot Rev. 2016 Jul;8(3):207-217. doi: 10.1177/1754073915586226. Epub 2015 May 28.
8
High emotional contagion and empathy are associated with enhanced detection of emotional authenticity in laughter.高情绪感染力和同理心与增强对笑声中情绪真实性的察觉有关。
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9
How many voices did you hear? Natural variability disrupts identity perception from unfamiliar voices.你听到了多少种声音?自然变异性会干扰对陌生声音的身份感知。
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10
Soundgen: An open-source tool for synthesizing nonverbal vocalizations.Soundgen:一个用于合成非言语发声的开源工具。
Behav Res Methods. 2019 Apr;51(2):778-792. doi: 10.3758/s13428-018-1095-7.

情绪真实性调节声音的情感和社会特质推断。

Emotional authenticity modulates affective and social trait inferences from voices.

机构信息

CICPSI, Faculdade de Psicologia, Universidade de Lisboa, Alameda da Universidade, 1649-013 Lisboa, Portugal.

Equipe de Neuro-Ethologie Sensorielle (ENES)/Centre de Recherche em Neurosciences de Lyon (CRNL), University of Lyon/Saint-Etienne, CNRS UMR5292, INSERM UMR_S 1028, 42023 Saint-Etienne, France.

出版信息

Philos Trans R Soc Lond B Biol Sci. 2021 Dec 20;376(1840):20200402. doi: 10.1098/rstb.2020.0402. Epub 2021 Nov 1.

DOI:10.1098/rstb.2020.0402
PMID:34719249
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8558771/
Abstract

The human voice is a primary tool for verbal and nonverbal communication. Studies on laughter emphasize a distinction between spontaneous laughter, which reflects a genuinely felt emotion, and volitional laughter, associated with more intentional communicative acts. Listeners can reliably differentiate the two. It remains unclear, however, if they can detect authenticity in other vocalizations, and whether authenticity determines the affective and social impressions that we form about others. Here, 137 participants listened to laughs and cries that could be spontaneous or volitional and rated them on authenticity, valence, arousal, trustworthiness and dominance. Bayesian mixed models indicated that listeners detect authenticity similarly well in laughter and crying. Speakers were also perceived to be more trustworthy, and in a higher arousal state, when their laughs and cries were spontaneous. Moreover, spontaneous laughs were evaluated as more positive than volitional ones, and we found that the same acoustic features predicted perceived authenticity and trustworthiness in laughter: high pitch, spectral variability and less voicing. For crying, associations between acoustic features and ratings were less reliable. These findings indicate that emotional authenticity shapes affective and social trait inferences from voices, and that the ability to detect authenticity in vocalizations is not limited to laughter. This article is part of the theme issue 'Voice modulation: from origin and mechanism to social impact (Part I)'.

摘要

人类的声音是言语和非言语交流的主要工具。对笑声的研究强调了自发性笑声和意愿性笑声之间的区别,前者反映了真实的情感,后者则与更具意向性的交际行为有关。听众可以可靠地区分这两种笑声。然而,目前尚不清楚他们是否能察觉其他声音的真实性,以及真实性是否决定了我们对他人形成的情感和社会印象。在这里,137 名参与者听取了可能是自发的或意愿的笑声和哭声,并对其真实性、情绪、唤醒度、可信度和支配力进行了评分。贝叶斯混合模型表明,听众在笑声和哭声中都能很好地察觉真实性。当人们的笑声和哭声是自发的时候,他们也被认为更值得信赖,而且情绪唤醒度更高。此外,自发的笑声比意愿的笑声评价更为积极,我们发现,相同的声学特征可以预测笑声中的感知真实性和可信度:高音、频谱可变性和较少的发声。对于哭声,声学特征与评分之间的关联则不太可靠。这些发现表明,情感的真实性塑造了从声音中得出的情感和社会特质推断,而且从声音中察觉真实性的能力并不仅限于笑声。本文是主题为“声音调制:从起源和机制到社会影响(第一部分)”的一部分。