Emotional authenticity modulates affective and social trait inferences from voices.
acoustics
authenticity
emotion
social traits
voice
Journal
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
ISSN: 1471-2970
Titre abrégé: Philos Trans R Soc Lond B Biol Sci
Pays: England
ID NLM: 7503623
Informations de publication
Date de publication:
20 12 2021
20 12 2021
Historique:
entrez:
1
11
2021
pubmed:
2
11
2021
medline:
19
3
2022
Statut:
ppublish
Résumé
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)'.
Identifiants
pubmed: 34719249
doi: 10.1098/rstb.2020.0402
pmc: PMC8558771
doi:
Banques de données
figshare
['10.6084/m9.figshare.c.5631307']
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
20200402Références
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