| Literature DB >> 32690113 |
Virginia A Marchman1, Adriana Weisleder2, Nereyda Hurtado3, Anne Fernald1.
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.Entities:
Mesh:
Year: 2020 PMID: 32690113 PMCID: PMC8178803 DOI: 10.1017/S0305000920000380
Source DB: PubMed Journal: J Child Lang ISSN: 0305-0009