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Record W4307291512 · doi:10.1017/s0305000922000460

Utterance-Initial Prosodic Differences Between Statements and Questions in Infant-Directed Speech

2022· article· en· W4307291512 on OpenAlexafffund
Susan Geffen, Kelly D. Burkinshaw, Angeliki Athanasopoulou, Suzanne Curtin

Bibliographic record

VenueJournal of Child Language · 2022
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsBrock UniversityUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCurtin University of TechnologyUniversity of Calgary
KeywordsUtterancePsychologyLinguisticsSentenceVariety (cybernetics)Meaning (existential)Class (philosophy)Part of speechArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Abstract Cross-linguistically, statements and questions broadly differ in syntactic organization. To learn the syntactic properties of each sentence type, learners might first rely on non-syntactic information. This paper analyzed prosodic differences between infant-directed wh -questions and statements to determine what kinds of cues might be available. We predicted there would be a significant difference depending on the first words that appear in wh -questions (e.g., two closed-class words; meaning words from a category that rarely changes) compared to the variety of first words found in statements. We measured F0, duration, and intensity of the first two words in statements and wh -questions in naturalistic speech from 13 mother-child dyads in the Brent corpus of the CHILDES database. Results found larger differences between sentence-types when the second word was an open-class not a closed-class word, suggesting a relationship between prosodic and syntactic information in an utterance-initial position that infants may use to make sentence-type distinctions.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.999

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)0.0020.000

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 head0.015
GPT teacher head0.340
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

Citations1
Published2022
Admission routes2
Has abstractyes

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