Big five personality perceptions from voices and faces: Impressions and kernels of truth.

We investigated the perception of Big Five personality traits from trait-average voices when traits were based either on speakers' self-ratings (Exp. 1, E1) or on other perceivers' ratings of perceived personality of the original voice samples (E2). Trait-average voices were created from a voice dat...

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Publicado en:Journal of Nonverbal Behavior Vol. 49; no. 1; pp. 125 - 155
Autores principales: Skuk, Verena G., Jacob, Isabell, Wientzek, Rebecca, Ward, Robert, Schweinberger, Stefan R.
Formato: Artículo
Publicado: Springer Nature Mar2025
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2025
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      pub: Springer Nature
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        10.1007/s10919-025-00480-5
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        atl: Big five personality perceptions from voices and faces: Impressions and kernels of truth.
      aug:
        au:
          Skuk, Verena G.
          Jacob, Isabell
          Wientzek, Rebecca
          Ward, Robert
          Schweinberger, Stefan R.
        affil:
          https://ror.org/05qpz1x62 Department for General Psychology and Cognitive Neuroscience, Institute of Psychology, Friedrich Schiller University of Jena, Am Steiger 3, Haus 1, 07743, Jena, Germany
          https://ror.org/05qpz1x62 Voice Research Unit, Friedrich Schiller University of Jena, Am Steiger 3, Haus 1, 07743, Jena, Germany
          https://ror.org/006jb1a24 Department of Psychology, Bangor University, LL57 2DG, Bangor, UK
          German Center for Mental Health (DZPG), Site Jena-Magdeburg-Halle, 07743, Jena, Germany
      su:
        Stereotypes
        Social perception
        Personality
        Individuality
        Disclosure
        Neuroses
        Face
        Descriptive statistics
        Experimental design
        Human voice
      sug:
        subj:
          Stereotypes
          Social perception
          Personality
          Individuality
          Disclosure
          Neuroses
          Face
          Descriptive statistics
          Experimental design
          Human voice
      keyword:
        Individual differences
        Psychology and Cognitive Sciences Psychology
        Trait perception
        Voice
        Voice averaging
        Individual differences
        Psychology and Cognitive Sciences Psychology
        Trait perception
        Voice
        Voice averaging
      ab: We investigated the perception of Big Five personality traits from trait-average voices when traits were based either on speakers' self-ratings (Exp. 1, E1) or on other perceivers' ratings of perceived personality of the original voice samples (E2). Trait-average voices were created from a voice database of 93 speakers (40 male, 53 female) using TANDEM-STRAIGHT n-way morphing. For speaker sex, trait and for two sentences, we created voice averages based on five speakers each, who scored either high or low on the target trait. We then measured perceivers' ability to discriminate high and low trait-averages per trait. We also assessed facial trait perception (E3) using the paradigm and the full facial composite images by Kramer and Ward (QJEP 63:2273-2287, 2010). In trait-average voices based on self-ratings (E1), extraversion (for female speakers) and neuroticism (for male speakers) were the only traits that could be discriminated above chance levels. For trait-average voices which were based on other perceivers´ personality ratings of individual voices (E2), all Big Five traits were discriminated with high accuracy, demonstrating stereotyping in the sense of consistent (though not necessarily valid) personality impressions from voices. By comparison with E1, we found substantially better perception of self-rated traits from faces (E3), for all traits except for openness, replicating Kramer and Ward (2010). Individual differences in trait perception were substantial, and there were small but significant correlations between facial and vocal trait perception skills in both E1 and E2. Overall, the present methodological approach may offer a promising window into personality perception from voices.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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