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Algorithmic voice transformations reveal the phonological basis of language-familiarity effects in cross-cultural emotion judgments

People have a well-described advantage in identifying individuals and emotions in their own culture, a phenomenon also known as the other-race and language-familiarity effect. However, it is unclear whether native-language advantages arise from genuinely enhanced capacities to extract relevant cues...

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Autores principales: Nakai, Tomoya, Rachman, Laura, Arias Sarah, Pablo, Okanoya, Kazuo, Aucouturier, Jean-Julien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10156011/
https://www.ncbi.nlm.nih.gov/pubmed/37134091
http://dx.doi.org/10.1371/journal.pone.0285028
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author Nakai, Tomoya
Rachman, Laura
Arias Sarah, Pablo
Okanoya, Kazuo
Aucouturier, Jean-Julien
author_facet Nakai, Tomoya
Rachman, Laura
Arias Sarah, Pablo
Okanoya, Kazuo
Aucouturier, Jean-Julien
author_sort Nakai, Tomoya
collection PubMed
description People have a well-described advantage in identifying individuals and emotions in their own culture, a phenomenon also known as the other-race and language-familiarity effect. However, it is unclear whether native-language advantages arise from genuinely enhanced capacities to extract relevant cues in familiar speech or, more simply, from cultural differences in emotional expressions. Here, to rule out production differences, we use algorithmic voice transformations to create French and Japanese stimulus pairs that differed by exactly the same acoustical characteristics. In two cross-cultural experiments, participants performed better in their native language when categorizing vocal emotional cues and detecting non-emotional pitch changes. This advantage persisted over three types of stimulus degradation (jabberwocky, shuffled and reversed sentences), which disturbed semantics, syntax, and supra-segmental patterns, respectively. These results provide evidence that production differences are not the sole drivers of the language-familiarity effect in cross-cultural emotion perception. Listeners’ unfamiliarity with the phonology of another language, rather than with its syntax or semantics, impairs the detection of pitch prosodic cues and, in turn, the recognition of expressive prosody.
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spelling pubmed-101560112023-05-04 Algorithmic voice transformations reveal the phonological basis of language-familiarity effects in cross-cultural emotion judgments Nakai, Tomoya Rachman, Laura Arias Sarah, Pablo Okanoya, Kazuo Aucouturier, Jean-Julien PLoS One Research Article People have a well-described advantage in identifying individuals and emotions in their own culture, a phenomenon also known as the other-race and language-familiarity effect. However, it is unclear whether native-language advantages arise from genuinely enhanced capacities to extract relevant cues in familiar speech or, more simply, from cultural differences in emotional expressions. Here, to rule out production differences, we use algorithmic voice transformations to create French and Japanese stimulus pairs that differed by exactly the same acoustical characteristics. In two cross-cultural experiments, participants performed better in their native language when categorizing vocal emotional cues and detecting non-emotional pitch changes. This advantage persisted over three types of stimulus degradation (jabberwocky, shuffled and reversed sentences), which disturbed semantics, syntax, and supra-segmental patterns, respectively. These results provide evidence that production differences are not the sole drivers of the language-familiarity effect in cross-cultural emotion perception. Listeners’ unfamiliarity with the phonology of another language, rather than with its syntax or semantics, impairs the detection of pitch prosodic cues and, in turn, the recognition of expressive prosody. Public Library of Science 2023-05-03 /pmc/articles/PMC10156011/ /pubmed/37134091 http://dx.doi.org/10.1371/journal.pone.0285028 Text en © 2023 Nakai et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Nakai, Tomoya
Rachman, Laura
Arias Sarah, Pablo
Okanoya, Kazuo
Aucouturier, Jean-Julien
Algorithmic voice transformations reveal the phonological basis of language-familiarity effects in cross-cultural emotion judgments
title Algorithmic voice transformations reveal the phonological basis of language-familiarity effects in cross-cultural emotion judgments
title_full Algorithmic voice transformations reveal the phonological basis of language-familiarity effects in cross-cultural emotion judgments
title_fullStr Algorithmic voice transformations reveal the phonological basis of language-familiarity effects in cross-cultural emotion judgments
title_full_unstemmed Algorithmic voice transformations reveal the phonological basis of language-familiarity effects in cross-cultural emotion judgments
title_short Algorithmic voice transformations reveal the phonological basis of language-familiarity effects in cross-cultural emotion judgments
title_sort algorithmic voice transformations reveal the phonological basis of language-familiarity effects in cross-cultural emotion judgments
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10156011/
https://www.ncbi.nlm.nih.gov/pubmed/37134091
http://dx.doi.org/10.1371/journal.pone.0285028
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