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Record W4224938348 · doi:10.3389/fpsyg.2022.874411

Learning to Recognize Unfamiliar Voices: An Online Study With 12- and 24-Month-Olds

2022· article· en· W4224938348 on OpenAlexafffund
Adriel John Orena, Asia Sotera Mader, Janet F. Werker

Bibliographic record

VenueFrontiers in Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsFraser HealthUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsIndexicalityPsychologyFace (sociological concept)CommunicationLinguisticsCognitive psychology

Abstract

fetched live from OpenAlex

Young infants are attuned to the indexical properties of speech: they can recognize highly familiar voices and distinguish them from unfamiliar voices. Less is known about how and when infants start to recognize unfamiliar voices, and to map them to faces. This skill is particularly challenging when portions of the speaker’s face are occluded, as is the case with masking. Here, we examined voice−face recognition abilities in infants 12 and 24 months of age. Using the online Lookit platform, children saw and heard four different speakers produce words with sonorous phonemes (high talker information), and words with phonemes that are less sonorous (low talker information). Infants aged 24 months, but not 12 months, were able to learn to link the voices to partially occluded faces of unfamiliar speakers, and only when the words were produced with high talker information. These results reveal that 24-month-old infants can encode and retrieve indexical properties of an unfamiliar speaker’s voice, and they can access this information even when visual access to the speaker’s mouth is blocked.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.313
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2022
Admission routes2
Has abstractyes

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