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Record W2791671258 · doi:10.1111/mbe.12162

Cascading and Multisensory Influences on Speech Perception Development

2018· article· en· W2791671258 on OpenAlexafffund
Dawoon Choi, Alexis K. Black, Janet F. Werker

Bibliographic record

VenueMind Brain and Education · 2018
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaCanadian Institute for Advanced Research
KeywordsPerceptionCognitive psychologyContext (archaeology)Speech perceptionSyntaxPsychologyOpenness to experienceLanguage acquisitionComputer scienceSocial psychologyArtificial intelligenceHistoryNeuroscience

Abstract

fetched live from OpenAlex

ABSTRACT Over the first weeks and months following birth, infants' initial, broad‐based perceptual sensitivities become honed to the characteristics of their native language. In this article, we review this process of emerging specialization within the context of a cascading “critical period” (CP) framework, in which periods of maximal openness to experience of different aspects of language occur at sequential, overlapping points in development. Importantly, as infants' experience of speech is not limited to auditory signals, but is informed by—for example—their experience of talking faces and their own oral motor movements, we review the trajectory of perceptual specialization in multisensory language processing. Throughout, we highlight the impact of increasing perceptual specialization on later language outcomes (e.g., word learning, foundations of syntax, literacy), and consider how the outcomes can be compromised if/when the timing of perceptual specialization has been perturbed.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.052
GPT teacher head0.378
Teacher spread0.326 · 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

Citations41
Published2018
Admission routes2
Has abstractyes

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