Neural indicators of articulator-specific sensorimotor influences on infant speech perception
Bibliographic record
Abstract
While there is increasing acceptance that even young infants detect correspondences between heard and seen speech, the common view is that oral-motor movements related to speech production cannot influence speech perception until infants begin to babble or speak. We investigated the extent of multimodal speech influences on auditory speech perception in prebabbling infants who have limited speech-like oral-motor repertoires. We used event-related potentials (ERPs) to examine how sensorimotor influences to the infant's own articulatory movements impact auditory speech perception in 3-mo-old infants. In experiment 1, there were ERP discriminative responses to phonetic category changes across two phonetic contrasts (bilabial-dental /ba/-/ɗa/; dental-retroflex /ɗa/-/ɖa/) in a mismatch paradigm, indicating that infants auditorily discriminated both contrasts. In experiment 2, inhibiting infants' own tongue-tip movements had a disruptive influence on the early ERP discriminative response to the /ɗa/-/ɖa/ contrast only. The same articulatory inhibition had contrasting effects on the perception of the /ba/-/ɗa/ contrast, which requires different articulators (the lips vs. the tongue) during production, and the /ɗa/-/ɖa/ contrast, whereby both phones require tongue-tip movement as a place of articulation. This articulatory distinction between the two contrasts plausibly accounts for the distinct influence of tongue-tip suppression on the neural responses to phonetic category change perception in definitively prebabbling, 3-mo-old, infants. The results showing a specificity in the relation between oral-motor inhibition and phonetic speech discrimination suggest a surprisingly early mapping between auditory and motor speech representation already in prebabbling infants.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".