Sensorimotor influences on speech perception in infancy
Bibliographic record
Abstract
The influence of speech production on speech perception is well established in adults. However, because adults have a long history of both perceiving and producing speech, the extent to which the perception-production linkage is due to experience is unknown. We addressed this issue by asking whether articulatory configurations can influence infants' speech perception performance. To eliminate influences from specific linguistic experience, we studied preverbal, 6-mo-old infants and tested the discrimination of a nonnative, and hence never-before-experienced, speech sound distinction. In three experimental studies, we used teething toys to control the position and movement of the tongue tip while the infants listened to the speech sounds. Using ultrasound imaging technology, we verified that the teething toys consistently and effectively constrained the movement and positioning of infants' tongues. With a looking-time procedure, we found that temporarily restraining infants' articulators impeded their discrimination of a nonnative consonant contrast but only when the relevant articulator was selectively restrained to prevent the movements associated with producing those sounds. Our results provide striking evidence that even before infants speak their first words and without specific listening experience, sensorimotor information from the articulators influences speech perception. These results transform theories of speech perception by suggesting that even at the initial stages of development, oral-motor movements influence speech sound discrimination. Moreover, an experimentally induced "impairment" in articulator movement can compromise speech perception performance, raising the question of whether long-term oral-motor impairments may impact perceptual development.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| 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".