ArticleBehavior research methods2018
Correlation and agreement between Language ENvironment Analysis (LENA™) and manual transcription for Dutch natural language recordings.
Article in Behavior research methods, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Accuracy of the Language Environment Analysis System Segmentation and Metrics: A Systematic Review.Journal of speech, language, and hearing research : JSLHR · 2020Pooled it
- Performance and Biases of the LENA and ACLEW Algorithms in Analyzing Language Environments in Down, Fragile X, Angelman Syndromes, and Populations at Elevated Likelihood for Autism.Developmental science · 2026Article
- Caregiver mental health is associated with early childhood language outcomes and perception bias in rural China.Scientific reports · 2026Article
- Validation of the Language ENvironment Analysis (LENA) Automated Speech Processing Algorithm Labels for Adult and Child Segments in a Sample of Families From India.Journal of speech, language, and hearing research : JSLHR · 2025Article
- Caregiver response types and children language outcomes in preschoolers with and without hearing loss in Aotearoa New Zealand.Journal of the Royal Society of New Zealand · 2025Article
- The Effect of LENA (Language ENvironment Analysis) for Children with Hearing Loss in Denmark including a Pilot Validation for the Danish Language.Journal of clinical medicine · 2024Article
- A comparison of automatic and manual measures of turn-taking in monolingual and bilingual contexts.Behavior research methods · 2024Article
- Fathers' unmodulated prosody in child-directed speech.The Journal of the Acoustical Society of America · 2023Article
- Does age moderate the influence of early life language experiences? A Naturalistic home observation study.Early childhood research quarterly · 2023Article
- The home language environment in rural China: variations across family characteristics.BMC public health · 2023Article
- The Brain Imaging for Global Health (BRIGHT) Project: Longitudinal cohort study protocol.Gates open research · 2023Article
- Automated measurement: The need for a more objective view of the speech and language of autistic children.Frontiers in human neuroscience · 2023Article
- Factors of parental investment in the home language environment in peri-urban China: A mixed methods study.PloS one · 2023Article
- Assessment of Communication Abilities in Four Children with Early Bilateral CIs in Clinical and Home Environments with LENA System: A Case Report.Children (Basel, Switzerland) · 2022Article
- Conversation Initiation of Mothers, Fathers, and Toddlers in their Natural Home Environment.Computer speech & language · 2022Article
- The home language environment and early language ability in rural Southwestern China.Frontiers in psychology · 2022Article
- Accuracy of the Language Environment Analyses (LENAJournal of child language · 2021Article
- A thorough evaluation of the Language Environment Analysis (LENA) system.Behavior research methods · 2021Article
- Variations in the Home Language Environment and Early Language Development in Rural China.International journal of environmental research and public health · 2021Article
- Associations between Bilingualism and Memory Generalization During Infancy: Does Socioeconomic Status Matter?Bilingualism (Cambridge, England) · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Language ENvironment Analysis system (LENA™) automatically analyzes the natural sound environments of children. Among other things, it estimates the amounts of adult words (AWC), child vocalizations (CV), conversational turns (CT), and electronic media (TV) that a child is exposed to. To assess LENA's reliability, we compared it to manual transcription. Specifically, we calculated the correlation and agreement between the LENA estimates and manual counts for 48 five-min audio samples. These samples were selected from eight day-long recordings of six Dutch-speaking children (ages 2-5). The correlations were strong for AWC, r = . 87, and CV, r = . 77, and comparatively low for CT, r = . 52, and TV, r = . 50. However, the agreement analysis revealed a constant bias in AWC counts, and proportional biases for CV and CT (i.e., the bias varied with the values for CV and CT). Agreement for detecting electronic media was poor. Moreover, the limits of agreement were wide for all four metrics. That is, the differences between LENA and the manual transcriptions for individual audio samples varied widely around the mean difference. This variation could indicate that LENA was affected by differences between the samples that did not equally affect the human transcribers. The disagreements and biases cast doubt on the comparability of LENA measurements across families and time, which is crucial for using LENA in research. Our sample is too small to conclude within which limits LENA's measurements are comparable, but it seems advisable to be cautious of factors that could systematically bias LENA's performance and thereby create confounds.
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