Mapping the Early Language Environment Using All-Day Recordings and Automated Analysis.

Purpose: This research provided a first-generation standardization of automated language environment estimates, validated these estimates against standard language assessments, and extended on previous research reporting language behavior differences across socioeconomic groups.

Method: Typically developing children between 2 to 48 months of age completed monthly, daylong recordings in their natural language environments over a span of approximately 6-38 months. The resulting data set contained 3,213 12-hr recordings automatically analyzed by using the Language Environment Analysis (LENA) System to generate estimates of (a) the number of adult words in the child's environment, (b) the amount of caregiver-child interaction, and (c) the frequency of child vocal output.

Results: Child vocalization frequency and turn-taking increased with age, whereas adult word counts were age independent after early infancy. Child vocalization and conversational turn estimates predicted 7%-16% of the variance observed in child language assessment scores. Lower socioeconomic status (SES) children produced fewer vocalizations, engaged in fewer adult-child interactions, and were exposed to fewer daily adult words compared with their higher socioeconomic status peers, but within-group variability was high.

Conclusions: The results offer new insight into the landscape of the early language environment, with clinical implications for identification of children at-risk for impoverished language environments.