ACOUSTIC ANALYSIS OF ORAL PRODUCTIONS OF INFANTS LATER DIAGNOSED WITH AUTISM AND THEIR MOTHER
Bibliographic record
Abstract
Research on early signs of autism in social interactions often focuses on infants' motor behaviors; few studies have focused on speech characteristics. This study examines infant-directed speech of mothers of infants later diagnosed with autism (LDA; n = 12) or of typically developing infants (TD; n = 11) as well as infants' productions (13 LDA, 13 TD). Since LDA infants appear to behave differently in the first months of life, it can affect the functioning of dyadic interactions, especially the first vocal productions, sensitive to expressiveness and emotions sharing. We assumed that in the first 6 months of life, prosodic characteristics (mean duration, mean pitch, and intonative contour types) will be different in dyads with autism. We extracted infants' and mothers' vocal productions from family home movies and analyzed the mean duration and pitch as well as the pitch contours in interactive episodes. Results show that mothers of LDA infants use relatively shorter productions as compared to mothers talking to TD infants. LDA infants' productions are not different in duration or pitch, but they use less complex modulated productions (i.e., those with more than two melodic modulations) than do TD. Further studies should focus on developmental profiles in the first year, analyzing prosody monthly.
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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 | 0.001 |
| 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".