2019
DOI: 10.1177/1747021819888064
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Sorting through the impact of familiarity when processing vocal identity: Results from a voice sorting task

Abstract: The present article reports on one experiment designed to examine the importance of familiarity when processing vocal identity. A voice sorting task was used with participants who were either personally familiar or unfamiliar with three speakers. The results suggested that familiarity supported both an ability to tell different instances of the same voice together, and to tell similar instances of different voices apart. In addition, the results suggested differences between the three speakers in terms of the … Show more

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Cited by 25 publications
(46 citation statements)
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References 68 publications
(124 reference statements)
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“…In keeping with previous studies on other aspects of voice perception (identity: Lavan, et al, 2016;Kreitewolf & Lavan, et al 2020;Lavan, Burston & Garrido, 2019;Lavan Burston, Merriman, et al, 2019;Stevenage, et al, 2020. Speech intelligibility: Domingo et al 2019Holmes et al, 2019;Holmes et al, 2018;Johnsrude et al, 2013;Kreitewolf et al, 2017), we found an overall familiarity advantage for age perception (see also Hunter & Fergusson, 2017) -note however, that familiarity interacted with identity (see below).…”
Section: Discussionsupporting
confidence: 91%
See 1 more Smart Citation
“…In keeping with previous studies on other aspects of voice perception (identity: Lavan, et al, 2016;Kreitewolf & Lavan, et al 2020;Lavan, Burston & Garrido, 2019;Lavan Burston, Merriman, et al, 2019;Stevenage, et al, 2020. Speech intelligibility: Domingo et al 2019Holmes et al, 2019;Holmes et al, 2018;Johnsrude et al, 2013;Kreitewolf et al, 2017), we found an overall familiarity advantage for age perception (see also Hunter & Fergusson, 2017) -note however, that familiarity interacted with identity (see below).…”
Section: Discussionsupporting
confidence: 91%
“…Advantages due to being familiar with a voice have been widely reported for a number of perceptual judgements in the voice and speech processing literature. For example, voice identity perception is less error-prone when listeners are familiar with a voice (voice discrimination: Lavan, Scott & McGettigan, 2016;Kreitewolf, Lavan, Obleser & McGettigan, 2020; voice identity sorting: Lavan, Burston & Garrido, 2019;Lavan Burston, Merriman, Ladwa, Knight & McGettigan, 2019;Stevenage, Symons, Fletcher & Coen, 2020). Interestingly, judgements of a person's social traits (e.g., their perceived trustworthiness or dominance) are not systematically affected by voice familiarity (Lavan, Mileva & McGettigan, 2020).…”
Section: Introductionmentioning
confidence: 99%
“…In contrast, unfamiliar listeners tend to systematically fail in "telling people together", thus perceiving variable voice recordings of the same person as many different people. This manifests in unfamiliar listeners making many more clusters than the true number of identities in the task (Lavan, Burston, & Garrido, 2019;, Stevenage, Symons, Fletcher & Coen, 2020. Similar evidence for familiarity advantages have also been reported for speaker discrimination tasks (Lavan, Scott & McGettigan, 2016).…”
Section: Introductionsupporting
confidence: 71%
“…For example, as in previous sorting studies, participants did not make many errors for telling people apart, leading to near-perfect performance in these measures. Future research may attempt to increase the difficulty of "telling people apart" by, for example, using less variable stimuli that sound less distinct from each other, both across and possibly also in within person (e.g., Stevenage et al, 2020). However, we note that changes to the stimuli will not only affect how well participants can tell people apart but will also affect "telling people together" (e.g., making this aspect of the task easier through decreased variability).…”
Section: Discussionmentioning
confidence: 99%
“…Recent studies investigating the effects of within-person variability on voice and face perception have highlighted further similarities between voice and face identity processing (For voices: Lavan, Burston, & Garrido, 2019 ; Lavan, Burston, Ladwa, et al, 2019 ; Lavan, Merriman, et al, 2019 ; Stevenage et al, 2020 , For faces: Andrews et al, 2015 ; Balas & Saville, 2017 ; Jenkins et al, 2011 ; Laurence et al, 2016 ; Redfern & Benton, 2017 ; Short et al, 2017 ; Zhou & Mondloch, 2016 ). Images of faces and recordings of voices can vary considerably from instance to instance ( Burton, 2013 ; Lavan, Burton, et al, 2019 ).…”
Section: Introductionmentioning
confidence: 99%