2021
DOI: 10.1037/xge0001019
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Trait evaluations of faces and voices: Comparing within- and between-person variability.

Abstract: Human faces and voices are rich sources of information that can vary in many different ways. Most of the literature on face/voice perception has focussed on understanding how people look and sound different to each other (between-person variability). However, recent studies highlight the ways in which the same person can look and sound different on different occasions (within-person variability). Across three experiments, we examined how within-and between-person variability relate to one another for social tr… Show more

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Cited by 18 publications
(26 citation statements)
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References 79 publications
(178 reference statements)
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“…The clear segregation of face space and trait space allows the same trait representation (e.g., trustworthy) to be excited independently by different types of sensory input. Thus, while the TIM framework was developed to explain first impressions from faces, the same architecture may be applied to understand other types of first impression, including those based on body shape [34] and vocal cues [36,37].…”
Section: Trait Inference Mappingmentioning
confidence: 99%
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“…The clear segregation of face space and trait space allows the same trait representation (e.g., trustworthy) to be excited independently by different types of sensory input. Thus, while the TIM framework was developed to explain first impressions from faces, the same architecture may be applied to understand other types of first impression, including those based on body shape [34] and vocal cues [36,37].…”
Section: Trait Inference Mappingmentioning
confidence: 99%
“…In the absence of any person-specific perceptual learning, however, the representation of strangers' faces may be particularly error-prone [104]. This feature of the model provides an elegant account of why different images of the same unfamiliar face (e.g., with different poses, different lighting conditions) sometimes elicit different trait attributions [37,109]. Different poses and different lighting conditions may produce different estimates of facial appearance and thereby excite different trait profiles.…”
Section: Boxmentioning
confidence: 99%
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“…Agreement in our study appears to be overall somewhat lower compared to previous studies of trait perception from voices (e.g.,Lavan, Mileva, Burton, Young, & McGettigan, 2021;Mileva et al, 2020;McAleer et al, 2014). This lower agreement is to be expected since most other studies have used voice stimuli with linguistic content (e.g., words or sentences; but seeRezlescu et al, 2015 who used vowels), while usually also sampling longer stimulus durations (~390ms in McAleer et al, 2014; stimuli duration of several seconds for…”
mentioning
confidence: 95%
“…Among these studies, some reports are showing that some impressions are already formed after surprisingly little exposure: For example, trait impressions and as well socially-relevant accent impressions are well-established after hearing the word "Hello" (~400ms of exposure, McAleer et al, 2014;Mahrholz et al, 2018;Purnell et al, 1999) or after exposure a single sustained vowel (Rezlescu et al, 2015). There are, however, only two studies that formally examine the time course of first impression formation from voices, including looking for the minimal exposure necessary to form impressions: For trait perception from voices, Mileva & Lavan (2021) establish that impressions of traits are indeed generally formed within 400ms, with impressions of dominance for male voices being more rapid (<50ms) and impressions of attractiveness for female voices being established by 200ms of exposure. Owren et al (2007) furthermore examined the time course over of how accuracy in gender perception from voices evolves.…”
Section: Introductionmentioning
confidence: 99%