Evidence map›Paper›PMID 38665246›Full record

ReviewCommunications psychology2023

A model for person perception from familiar and unfamiliar voices.

Nadine Lavan, Carolyn McGettigan

Abstract readReview
In one paragraph

Review in Communications psychology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Can conceptual beliefs shape impressions from voices?Psychonomic bulletin & review · 2026
    Article
  3. Time after time: Voice perception from first impressions to identity recognition.Quarterly journal of experimental psychology (2006) · 2025
    Review
  4. Autistic adults form first impressions from voices in similar ways to non-autistic adults.British journal of psychology (London, England : 1953) · 2025
    Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. The time course of person perception from voices in the brain.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Nadine LavanDepartment of Experimental and Biological Psychology, Queen Mary University of London, London, UK.ORCID 0000-0001-7569-0817
Carolyn McGettiganDepartment of Speech, Hearing, and Phonetic Sciences, University College London, London, UK.

Funding

Wellcome Trust
6 · The paper itself

Abstract

When hearing a voice, listeners can form a detailed impression of the person behind the voice. Existing models of voice processing focus primarily on one aspect of person perception - identity recognition from familiar voices - but do not account for the perception of other person characteristics (e.g., sex, age, personality traits). Here, we present a broader perspective, proposing that listeners have a common perceptual goal of perceiving who they are hearing, whether the voice is familiar or unfamiliar. We outline and discuss a model - the Person Perception from Voices (PPV) model - that achieves this goal via a common mechanism of recognising a familiar person, persona, or set of speaker characteristics. Our PPV model aims to provide a more comprehensive account of how listeners perceive the person they are listening to, using an approach that incorporates and builds on aspects of the hierarchical frameworks and prototype-based mechanisms proposed within existing models of voice identity recognition.

Indexed as

Human behaviourPerception

Identifiers

PMID38665246
PMCPMC11041786

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.