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Record W2040904119 · doi:10.1121/1.2932885

Is there a sensitive period for representation of phoneme sequences

2008· article· en· W2040904119 on OpenAlexaff
Mary Anne Welton, Annabel J. Cohen

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2008
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsMandarin ChinesePeriod (music)Representation (politics)LinguisticsPsychologyPerceptionWord (group theory)SurpriseComputer scienceCommunication

Abstract

fetched live from OpenAlex

A key issue in development of speech perception and production concerns the possible existence of an early sensitive period that facilitates language acquisition. Spoken language acquisition entails representation of grammatical sequences of phonemes. In a two-phase experiment, 120 participants in three age groups (pre-adolescents, adolescents, young adults) were presented with 64 words, 16 each of English, English pronounceable non-words, Spanish, and Mandarin. The task was to determine if the word was English. All age groups performed well, indicating that the words had been attended. A subsequent surprise recognition phase presented 64 words again, one half of which were old and one half new. Participants judged whether each word had previously been presented. Here performance overall was poorest for Spanish and Mandarin, and children performed relatively more poorly on English non-words as compared to the older groups, but showed no age-relative disadvantage for Chinese. Arguing that evidence for a sensitive period arises if children perform relatively better than older participants on foreign words as compared to English words or English non-words, the recognition results are consistent with the proposal of a sensitive period for phoneme sequence representation. The paradigm provides a new way of examining the sensitive period hypothesis. (supported by NSERC)

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.287

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 studies0.0000.001
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 head0.029
GPT teacher head0.318
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.

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

Citations0
Published2008
Admission routes1
Has abstractyes

Explore more

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