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Record W1968491442 · doi:10.1121/1.4783052

Phonetic representation of frequent function words in 8-month-old infants

2004· article· en· W1968491442 on OpenAlexaff
Rushen Shi, Janet F. Werker, Anne Cutler

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2004
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of British ColumbiaUniversité du Québec à Montréal
Fundersnot available
KeywordsFunctorLinguisticsKannadaMathematicsNonsenseActive listeningComputer sciencePsychologyPure mathematicsCommunicationArtificial intelligenceBiologyPhilosophy

Abstract

fetched live from OpenAlex

Recent work by a number of researchers showed that even preverbal infants detect and recognize functors in continuous speech. In our research, English-learning infants aged 11 to 13 months, but not 8 months, recognized frequent and infrequent functors as a class, and represented them in segmental detail (Shi et al., 2003; Shi et al., 2004). Here we report a study on 8-month-old infants’ recognition and representation of high versus low frequency functors. Infants heard sequences containing a lexical word preceded by a high frequency functor ‘‘the,’’ versus a nonsense functor ‘‘kuh,’’ differing from ‘‘the’’ only in the initial consonant, with the prosody unchanged. Another group of 8-month-olds heard sequences containing a lexical word preceded by a low frequency functor ‘‘its,’’ versus a nonsense functor ‘‘ots.’’ Recognition of functors would be indicated by longer listening time to sequences containing real functors. Results reveal no differential listening time between ‘‘the+lexical word(LW)’’ and ‘‘kuh+LW,’’ nor between ‘‘its+LW’’ and ‘‘ots+LW;’’ however, ‘‘the+LW’’ and ‘‘kuh+LW’’ together induced longer listening time than ‘‘its+LW’’ and ‘‘ots+LW.’’ We conclude that 8-month olds recognize the frequent, familiar ‘‘the’’ in continuous speech, but it is underspecified phonetically in infants’ initial lexicon. Our previous work indicates detailed specification by 11 months.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.283

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)0.0000.000

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 head0.013
GPT teacher head0.285
Teacher spread0.272 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicLanguage Development and DisordersFrench-language works237,207