How sign language expertise can influence the effects of face masks on non-linguistic characteristics

Autor: Wee Kiat Lau, Jana Chalupny, Klaudia Grote, Anke Huckauf
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Cognitive Research, Vol 7, Iss 1, Pp 1-17 (2022)
Druh dokumentu: article
ISSN: 2365-7464
DOI: 10.1186/s41235-022-00405-6
Popis: Abstract Face masks occlude parts of the face which hinders social communication and emotion recognition. Since sign language users are known to process facial information not only perceptually but also linguistically, examining face processing in deaf signers may reveal how linguistic aspects add to perceptual information. In general, signers could be born deaf or acquire hearing loss later in life. For this study, we focused on signers who were born deaf. Specifically, we analyzed data from a sample of 59 signers who were born deaf and investigated the impacts of face masks on non-linguistic characteristics of the face. Signers rated still-image faces with and without face masks for the following characteristics: arousal and valence of three facial expressions (happy, neutral, sad), invariant characteristics (DV:sex, age), and trait-like characteristics (attractiveness, trustworthiness, approachability). Results indicated that, when compared to masked faces, signers rated no-masked faces with stronger valence intensity across all expressions. Masked faces also appeared older, albeit a tendency to look more approachable. This experiment was a repeat of a previous study conducted on hearing participants, and a post hoc comparison was performed to assess rating differences between signers and hearing people. From this comparison, signers exhibited a larger tendency to rate facial expressions more intensely than hearing people. This suggests that deaf people perceive more intense information from facial expressions and face masks are more inhibiting for deaf people than hearing people. We speculate that deaf people found face masks more approachable due to societal norms when interacting with people wearing masks. Other factors like age and face database’s legitimacy are discussed.
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