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Mapping the Early Language Environment Using All-Day Recordings and Automated Analysis
Jill Gilkerson1, Jeffrey A Richards1, Steven F Warren2
1LENA Research Foundation, Boulder, CO.
American Journal of Speech-Language Pathology
|April 19, 2017
Summary
Automated language environment analysis using the LENA System provides reliable estimates of early language exposure. These estimates reveal socioeconomic disparities in language interactions, crucial for identifying at-risk children.
Area of Science:
- Child Development
- Linguistics
- Speech-Language Pathology
Background:
- Early language exposure significantly impacts child development.
- Previous research indicated socioeconomic disparities in language environments.
- Automated analysis offers a scalable method for assessing language environments.
Purpose of the Study:
- Standardize automated language environment estimates.
- Validate automated estimates against established language assessments.
- Investigate socioeconomic differences in early language exposure.
Main Methods:
- Longitudinal, daylong recordings of typically developing children (2-48 months).
- Analysis of 3,213 recordings using the Language Environment Analysis (LENA) System.
- Estimation of adult words, caregiver-child interactions, and child vocalizations.
Main Results:
- Child vocalizations and turn-taking increased with age.
- Automated estimates predicted 7%-16% of language assessment score variance.
- Lower socioeconomic status children had reduced language exposure and interaction, with high within-group variability.
Conclusions:
- Automated language environment analysis offers valuable insights.
- Findings highlight clinical implications for identifying children at risk for language delays.
- Early language environment characteristics are linked to developmental outcomes.