Infant‐Directed Speech Is Modulated by Infant Feedback
Bibliographic record
Abstract
When mothers engage in infant‐directed (ID) speech, their voices change in a number of characteristic ways, including adopting a higher overall pitch. Studies have examined these acoustical cues and have tested infants' preferences for ID speech. However, little is known about how these cues change with maternal sensitivity to infant feedback in the context of interaction. In this study, each mother watched her infant (located in an adjacent sound booth) on a video screen and talked to him or her through a microphone. The mother believed that her infant could hear her voice and she attempted to make her infant happy through her vocalizations. In reality, the infant could not hear her voice. The mother's ID speech was analyzed in real time for changes in mean pitch. For half of the infant–mother dyads an experimenter surreptitiously positively engaged the infant when the voice analysis revealed a rise in pitch, thereby producing positive reinforcement to the mother for natural higher pitched ID speech. The other half were reinforced for lower pitched ID speech. Mothers raised their pitch significantly more in the former than the latter condition, illustrating that the pitch of ID speech is dynamically affected by feedback from the infant.
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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 | 0.004 |
| 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 | 0.000 |
| 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".