Developmental Changes in Infants’ Ability to Cope with Dialect Variation in Word Recognition
Bibliographic record
Abstract
Toward the end of their first year of life, infants' overly specified word representations are thought to give way to more abstract ones, which helps them to better cope with variation not relevant to word identity (e.g., voice and affect). This developmental change may help infants process the ambient language more efficiently, thus enabling rapid gains in vocabulary growth. One particular kind of variability that infants must accommodate is that of dialectal accent, because most children will encounter speakers from different regions and backgrounds. In this study, we explored developmental changes in infants' ability to recognize words in continuous speech by familiarizing them with words spoken by a speaker of their own region (North Midland-American English) or a different region (Southern Ontario Canadian English), and testing them with passages spoken by a speaker of the opposite dialectal accent. Our results demonstrate that 12- but not 9-month-olds readily recognize words in the face of dialectal variation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".