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Accuracy of the Language Environment Analyses (LENATM) system for estimating child and adult speech in laboratory settings

Published online by Cambridge University Press:  21 July 2020

Virginia A. MARCHMAN
Affiliation:
Stanford University, USA
Adriana WEISLEDER
Affiliation:
Northwestern University, USA
Nereyda HURTADO
Affiliation:
Grail Family Services, USA
Anne FERNALD
Affiliation:
Stanford University, USA
Corresponding
E-mail address:

Abstract

Laboratory observations are a mainstay of language development research, but transcription is costly. We test whether speech recognition technology originally designed for day-long contexts can be usefully applied to this use-case. We compared automated adult word and child vocalization counts from Language Environment Analysis (LENATM) to those of transcribers in 20-minute play sessions with Spanish-speaking dyads (n = 104) at 1;7 and 2;2. For adult words, results indicated moderate associations but large absolute differences. Associations for child vocalizations were weaker with larger absolute discrepancies. LENA has moderate potential to ease the burden of transcription in some research and clinical applications.

Type
Brief Research Report
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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