Automated Language Environment Analysis: A Research Synthesis Purpose The Language Environment Analysis (LENA®) represents a breakthrough in automatic speech detection because it makes one's language environment, what adults and children actually hear and say, efficiently measurable. The purpose of this article was to examine (a) current dimensions of LENA research, (b) LENA's sensitivity to differences in populations ... Review Article
Newly Published
Review Article  |   March 28, 2018
Automated Language Environment Analysis: A Research Synthesis
 
Author Affiliations & Notes
  • Charles R. Greenwood
    Juniper Gardens Children's Project, The University of Kansas, Kansas City
  • Alana G. Schnitz
    Juniper Gardens Children's Project, The University of Kansas, Kansas City
  • Dwight Irvin
    Juniper Gardens Children's Project, The University of Kansas, Kansas City
  • Shu Fe Tsai
    National University of Tainan, Taiwan
  • Judith J. Carta
    Juniper Gardens Children's Project, The University of Kansas, Kansas City
  • Disclosure: Charles Greenwood is a voluntary member of the LENA Research Foundation's Scientific Advisory Board.
    Disclosure: Charles Greenwood is a voluntary member of the LENA Research Foundation's Scientific Advisory Board. ×
  • Correspondence to Charles R. Greenwood: greenwood@ku.edu
  • Editor-in-Chief: Krista Wilkinson
    Editor-in-Chief: Krista Wilkinson×
  • Editor: Cynthia Cress
    Editor: Cynthia Cress×
Article Information
Cultural & Linguistic Diversity / School-Based Settings / Research Issues, Methods & Evidence-Based Practice / Newly Published / Review Article
Review Article   |   March 28, 2018
Automated Language Environment Analysis: A Research Synthesis
American Journal of Speech-Language Pathology, Newly Published. doi:10.1044/2017_AJSLP-17-0033
History: Received March 14, 2017 , Revised July 11, 2017 , Accepted November 29, 2017
 
American Journal of Speech-Language Pathology, Newly Published. doi:10.1044/2017_AJSLP-17-0033
History: Received March 14, 2017; Revised July 11, 2017; Accepted November 29, 2017

Purpose The Language Environment Analysis (LENA®) represents a breakthrough in automatic speech detection because it makes one's language environment, what adults and children actually hear and say, efficiently measurable. The purpose of this article was to examine (a) current dimensions of LENA research, (b) LENA's sensitivity to differences in populations and language environments, and (c) what has been achieved in closing the Word Gap.

Method From electronic and human searches, 83 peer-reviewed articles using LENA were identified, and 53 met inclusionary criteria and were included in a systematic literature review. Each article reported results of 1 study.

Results Originally developed to make natural language research more efficient and feasible, systematic review identified a broad landscape of relevant LENA findings focused primarily on the environments and communications of young children but also older adults and teachers. LENA's automated speech indicators (adult input, adult–child interaction, and child production) and the audio environment were shown to meet high validity standards, including accuracy, sensitivity to individual differences, and differences in populations, settings, contexts within settings, speakers, and languages. Researchers' own analyses of LENA audio recordings have extended our knowledge of microlevel processes in adult–child interaction. To date, intervention research using LENA has consisted of small pilot experiments, primarily on the effects of brief parent education plus quantitative linguistic feedback to parents.

Conclusion Evidence showed that automated analysis has made a place in the repertoire of language research and practice. Implications, limitations, and future research are discussed.

Acknowledgments
Preparation of this synthesis was supported by the Health Resources and Services Administration, U.S. Department of Health and Human Services Grant UA6MC 27762, Bridging the Word Gap Research Network (BWGRN) to The University of Kansas. Support for preparation of this manuscript was also provided by the Kansas Intellectual and Developmental Disabilities Research Center (HD002528), Schiefelbusch Institute for Life Span Studies, The University of Kansas. This information or content and conclusions are those of the authors and should not be construed as the official position or policy of nor should any endorsements be inferred by the Health Resources and Services Administration, U.S. Department of Health and Human Services, or the U.S. government. The authors acknowledge the contributions of their co-investigator in the BWGRN (Dale Walker). The authors also acknowledge the contributions of BWGRN Workgroup 6: measurement, design, and analysis members, including Stephen Crutchfield. The authors also thank the BWGRN synthesis team, Samantha Sepulveda, Melissa Kurrle, and Emily Meyer, for their comprehensive effort in creating a literature base. Thanks are due Shye Reynolds for software/web programming support. The authors acknowledge the contribution of Jill Gilkerson, the LENA Research Foundation, regarding article search and updates.
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