Acoustic signatures of communicative dimensions in codified mother-infant interactions
Bibliographic record
Abstract
Nursery rhymes, lullabies, or traditional stories are pieces of oral tradition that constitute an integral part of communication between caregivers and preverbal infants. Caregivers use a distinct acoustic style when singing or narrating to their infants. Unlike spontaneous infant-directed (ID) interactions, codified interactions benefit from highly stable acoustics due to their repetitive character. The aim of the study was to determine whether specific combinations of acoustic traits (i.e., vowel pitch, duration, spectral structure, and their variability) form characteristic "signatures" of different communicative dimensions during codified interactions, such as vocalization type, interactive stimulation, and infant-directedness. Bayesian analysis, applied to over 14 000 vowels from codified live interactions between mothers and their 6-months-old infants, showed that a few acoustic traits prominently characterize arousing vs calm interactions and sung vs spoken interactions. While pitch and duration and their variation played a prominent role in constituting these signatures, more linguistic aspects such as vowel clarity showed small or no effects. Infant-directedness was identifiable in a larger set of acoustic cues than the other dimensions. These findings provide insights into the functions of acoustic variation of ID communication and into the potential role of codified interactions for infants' learning about communicative intent and expressive forms typical of language and music.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".