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 ... Clinical Focus
Clinical Focus  |   May 17, 2017
Mapping the Early Language Environment Using All-Day Recordings and Automated Analysis
 
Author Affiliations & Notes
  • Jill Gilkerson
    LENA Research Foundation, Boulder, CO
  • Jeffrey A. Richards
    LENA Research Foundation, Boulder, CO
  • Steven F. Warren
    Life Span Institute, University of Kansas, Lawrence
  • Judith K. Montgomery
    Department of Communication Sciences and Disorders, Chapman University, Orange, CA
  • Charles R. Greenwood
    Juniper Garden's Children's Project, University of Kansas, Kansas City
  • D. Kimbrough Oller
    School of Communication Sciences and Disorders and Institute for Intelligent Systems, University of Memphis, TN
    Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg, Austria
  • John H. L. Hansen
    School of Engineering and Computer Science, University of Texas at Dallas
  • Terrance D. Paul
    LENA Research Foundation, Boulder, CO
  • Disclosure: The authors have declared that no competing interests existed at the time of publication.
    Disclosure: The authors have declared that no competing interests existed at the time of publication. ×
  • Correspondence to Jill Gilkerson: jillgilkerson@lenafoundation.org
  • Editor: Krista Wilkinson
    Editor: Krista Wilkinson×
  • Associate Editor: Cynthia Cress
    Associate Editor: Cynthia Cress×
Article Information
Development / School-Based Settings / Research Issues, Methods & Evidence-Based Practice / Normal Language Processing / Speech, Voice & Prosody / Clinical Focus
Clinical Focus   |   May 17, 2017
Mapping the Early Language Environment Using All-Day Recordings and Automated Analysis
American Journal of Speech-Language Pathology, May 2017, Vol. 26, 248-265. doi:10.1044/2016_AJSLP-15-0169
History: Received October 29, 2015 , Revised April 5, 2016 , Accepted October 31, 2016
 
American Journal of Speech-Language Pathology, May 2017, Vol. 26, 248-265. doi:10.1044/2016_AJSLP-15-0169
History: Received October 29, 2015; Revised April 5, 2016; Accepted October 31, 2016
Web of Science® Times Cited: 3

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.

Acknowledgments
This research was funded by the LENA Research Foundation, a nonprofit 501(c)(3) public charity. We gratefully acknowledge the Paul family for their wisdom and philanthropy, without which none of this work would have been possible; the LENA parents and children; the members of the LENA Scientific Advisory Board; and LENA Research Foundation employees past and present who contributed to this study.
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