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Record W1977810166 · doi:10.1121/1.4808930

Frequency factor in the segmentation of function words in French-learning infants

2006· article· en· W1977810166 on OpenAlexaffabout
Rushen Shi, Mélanie Lepage, Bruno Gauthier, Alexandra Marquis

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2006
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsFunctorSegmentationMathematicsFunction (biology)AudiologyPsychologyComputer scienceArtificial intelligenceMedicinePure mathematicsBiology

Abstract

fetched live from OpenAlex

Previous work showed that 8-month-old French-learning infants segment both highly and moderately frequent function words from continuous speech [Shi and Gauthier, J. Acoust. Soc. Am. 117, 2426 (2005)]. In the present study we examine if high-frequency function words are segmented by even younger infants. Participants were 6-month-old Quebec-French-learning infants. As in the previous study, infants in the high-frequency condition were familiarized with a target functor (des or la) and were then tested with phrases containing the target versus those containing the nontarget. Thus, for infants familiarized to la, la-phrases were the target phrases and des-phrases were the nontarget phrases during Test. The reverse was the case when des was the familiarization target. The lower-frequency condition included a target functor mes versus ta (prosodically analogous to the functors in the high-frequency condition). The results show that 6-month-olds listened significantly longer to phrases containing the familiarized target than those containing the nontarget during Test, suggesting that they segmented the target. No difference was observed in the lower-frequency condition. Thus, while 8-month-olds segmented both high- and lower-frequency functors [Shi and Gauthier, J. Acoust. Soc. Am. 117, 2426 (2005)], 6-month-olds showed evidence of segmentation only for high-frequency functors. These findings suggest that frequency is a determining factor in the development of the segmentation of function words.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.010
GPT teacher head0.271
Teacher spread0.261 · 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

Citations1
Published2006
Admission routes2
Has abstractyes

Explore more

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