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. 2018 Jun 19;61(6):1369-1380.
doi: 10.1044/2018_JSLHR-S-17-0287.

Infant-Mother Acoustic-Prosodic Alignment and Developmental Risk

Affiliations

Infant-Mother Acoustic-Prosodic Alignment and Developmental Risk

Amanda Seidl et al. J Speech Lang Hear Res. .

Abstract

Purpose: One promising early marker for autism and other communicative and language disorders is early infant speech production. Here we used daylong recordings of high- and low-risk infant-mother dyads to examine whether acoustic-prosodic alignment as well as two automated measures of infant vocalization are related to developmental risk status indexed via familial risk and developmental progress at 36 months of age.

Method: Automated analyses of the acoustics of daylong real-world interactions were used to examine whether pitch characteristics of one vocalization by the mother or the child predicted those of the vocalization response by the other speaker and whether other features of infants' speech in daylong recordings were associated with developmental risk status or outcomes.

Results: Low-risk and high-risk dyads did not differ in the level of acoustic-prosodic alignment, which was overall not significant. Further analyses revealed that acoustic-prosodic alignment did not predict infants' later developmental progress, which was, however, associated with two automated measures of infant vocalizations (daily vocalizations and conversational turns).

Conclusions: Although further research is needed, these findings suggest that automated measures of vocalizations drawn from daylong recordings are a possible early identification tool for later developmental progress/concerns.

Supplemental material: https://osf.io/cdn3v/.

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Figures

Figure 1.
Figure 1.
SecondIQR as a function of FirstIQR for each group. Each point represents f0 ranges in a pair of vocalizations (e.g., the f0 range measured in a vocalization uttered by the mother in the x axis, the f0 range in the child's next vocalization as predicted by the main mixed model—see main text for further details on the models). The regression lines represent linear fits between these two variables.
Figure 2.
Figure 2.
Individual percentiles for conversational turns as a function of the child's outcome status. To facilitate inspection, observations have been jittered along the x-axis.
Figure 3.
Figure 3.
Individual percentiles for daily vocalization count as a function of the child's outcome status. To facilitate inspection, observations have been jittered along the x-axis.

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