The interaction between acoustic salience and language experience in developmental speech perception: evidence from nasal place discrimination
Bibliographic record
Abstract
Previous research suggests that infant speech perception reorganizes in the first year: young infants discriminate both native and non-native phonetic contrasts, but by 10-12 months difficult non-native contrasts are less discriminable whereas performance improves on native contrasts. In the current study, four experiments tested the hypothesis that, in addition to the influence of native language experience, acoustic salience also affects the perceptual reorganization that takes place in infancy. Using a visual habituation paradigm, two nasal place distinctions that differ in relative acoustic salience, acoustically robust labial-alveolar [ma]-[na] and acoustically less salient alveolar-velar [na]-[ enga], were presented to infants in a cross-language design. English-learning infants at 6-8 and 10-12 months showed discrimination of the native and acoustically robust [ma]-[na] (Experiment 1), but not the non-native (in initial position) and acoustically less salient [na]-[ enga] (Experiment 2). Very young (4-5-month-old) English-learning infants tested on the same native and non-native contrasts also showed discrimination of only the [ma]-[na] distinction (Experiment 3). Filipino-learning infants, whose ambient language includes the syllable-initial alveolar (/n/)-velar (/ eng/) contrast, showed discrimination of native [na]-[ enga] at 10-12 months, but not at 6-8 months (Experiment 4). These results support the hypothesis that acoustic salience affects speech perception in infancy, with native language experience facilitating discrimination of an acoustically similar phonetic distinction [na]-[ enga]. We discuss the implications of this developmental profile for a comprehensive theory of speech perception in infancy.
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 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".