The effects of voicing and position in infants’ perception of coda consonants
Bibliographic record
Abstract
Infants’ ability to discriminate contrasting acoustic information has been demonstrated with many of the speech contrasts found in the world’s languages. However, this ability seems to be positionally constrained. Contrasts in onsets are discriminated by young infants, but coda contrasts are not discriminated until around 16- to 20-months [Zamuner (2006)]. Here we examine whether the contrast and the position influence discrimination in younger infants. We tested 64 12-month-olds’ discrimination of voiceless (/p/, /k/), or voiced stops (/b/, /g/) in either word-final (VC; Exp. 1) or word-medial (VCCV; Exp. 2) position. Experiment 1 habituated infants to ap or ak (voiceless) or to ab or ag (voiced). At test, infants heard the same token presented during habituation (same) and a novel token (switch). Planned comparisons revealed that only infants in the voiced condition looked longer to the switch than the same trial (p < 0.05). In experiment 2, infants heard apta or akta (voiceless) or abta or agta (voiced), but no effects of trial type were found, suggesting that the perceptual advantage in word-final position does not exist in word-medially. Thus, in word-final coda position voiced stops are more acoustically salient than voiceless stops, providing infants with added information to aid in discrimination.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".