Do nonlinear vocal phenomena signal negative valence or high emotion intensity?

acoustic communication context emotion nonlinear vocal phenomena nonverbal vocalizations

Journal

Royal Society open science
ISSN: 2054-5703
Titre abrégé: R Soc Open Sci
Pays: England
ID NLM: 101647528

Informations de publication

Date de publication:
Dec 2020
Historique:
received: 23 07 2020
accepted: 05 11 2020
entrez: 25 1 2021
pubmed: 26 1 2021
medline: 26 1 2021
Statut: epublish

Résumé

Nonlinear vocal phenomena (NLPs) are commonly reported in animal calls and, increasingly, in human vocalizations. These perceptually harsh and chaotic voice features function to attract attention and convey urgency, but they may also signal aversive states. To test whether NLPs enhance the perception of negative affect or only signal high arousal, we added subharmonics, sidebands or deterministic chaos to 48 synthetic human nonverbal vocalizations of ambiguous valence: gasps of fright/surprise, moans of pain/pleasure, roars of frustration/achievement and screams of fear/delight. In playback experiments (

Identifiants

pubmed: 33489278
doi: 10.1098/rsos.201306
pii: rsos201306
pmc: PMC7813245
doi:

Types de publication

Journal Article

Langues

eng

Pagination

201306

Informations de copyright

© 2020 The Authors.

Déclaration de conflit d'intérêts

The authors report no competing interests.

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Auteurs

Andrey Anikin (A)

Division of Cognitive Science, Lund University, Lund, Sweden.
Equipe de Neuro-Ethologie Sensorielle (ENES) / Centre de Recherche en Neurosciences de Lyon (CRNL), University of Lyon/Saint-Etienne, CNRS UMR5292, INSERM UMR_S 1028, Saint-Etienne, France.

Katarzyna Pisanski (K)

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

David Reby (D)

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

Classifications MeSH