Automated Language Environment Analysis: A Research Synthesis

Charles R Greenwood, Alana G Schnitz, Dwight Irvin, Shu Fe Tsai, Judith J Carta
American Journal of Speech-language Pathology 2018 May 3, 27 (2): 853-867

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.

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