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How Do You Say ‘Hello’? Personality Impressions from Brief Novel Voices

Overview of attention for article published in PLOS ONE, March 2014
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Title
How Do You Say ‘Hello’? Personality Impressions from Brief Novel Voices
Published in
PLOS ONE, March 2014
DOI 10.1371/journal.pone.0090779
Pubmed ID
Authors

Phil McAleer, Alexander Todorov, Pascal Belin

Abstract

On hearing a novel voice, listeners readily form personality impressions of that speaker. Accurate or not, these impressions are known to affect subsequent interactions; yet the underlying psychological and acoustical bases remain poorly understood. Furthermore, hitherto studies have focussed on extended speech as opposed to analysing the instantaneous impressions we obtain from first experience. In this paper, through a mass online rating experiment, 320 participants rated 64 sub-second vocal utterances of the word 'hello' on one of 10 personality traits. We show that: (1) personality judgements of brief utterances from unfamiliar speakers are consistent across listeners; (2) a two-dimensional 'social voice space' with axes mapping Valence (Trust, Likeability) and Dominance, each driven by differing combinations of vocal acoustics, adequately summarises ratings in both male and female voices; and (3) a positive combination of Valence and Dominance results in increased perceived male vocal Attractiveness, whereas perceived female vocal Attractiveness is largely controlled by increasing Valence. Results are discussed in relation to the rapid evaluation of personality and, in turn, the intent of others, as being driven by survival mechanisms via approach or avoidance behaviours. These findings provide empirical bases for predicting personality impressions from acoustical analyses of short utterances and for generating desired personality impressions in artificial voices.

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Mendeley readers

Mendeley readers

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Geographical breakdown

Country Count As %
United Kingdom 7 2%
Canada 2 <1%
Japan 2 <1%
United States 2 <1%
Austria 1 <1%
Estonia 1 <1%
Netherlands 1 <1%
Hungary 1 <1%
Luxembourg 1 <1%
Other 0 0%
Unknown 357 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 87 23%
Student > Bachelor 62 17%
Researcher 43 11%
Student > Master 39 10%
Professor > Associate Professor 16 4%
Other 62 17%
Unknown 66 18%
Readers by discipline Count As %
Psychology 133 35%
Linguistics 23 6%
Business, Management and Accounting 18 5%
Social Sciences 18 5%
Agricultural and Biological Sciences 17 5%
Other 77 21%
Unknown 89 24%