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How much does prosody help word segmentation? A simulation study on infant-directed speech
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In: ISSN: 0010-0277 ; EISSN: 1873-7838 ; Cognition ; https://hal.archives-ouvertes.fr/hal-03498888 ; Cognition, Elsevier, 2022, 219, pp.104961. ⟨10.1016/j.cognition.2021.104961⟩ (2022)
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Supplementary materials: Factors structuring lexical development in toddlers: The effects of parental education, language exposure, and age ...
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Is there a bilingual disadvantage for word segmentation? A computational modeling approach
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In: ISSN: 0305-0009 ; EISSN: 1469-7602 ; Journal of Child Language ; https://hal.archives-ouvertes.fr/hal-03498905 ; Journal of Child Language, Cambridge University Press (CUP), 2021, pp.1-28. ⟨10.1017/S0305000921000568⟩ (2021)
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SCALa: A blueprint for computational models of language acquisition in social context
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In: ISSN: 0010-0277 ; EISSN: 1873-7838 ; Cognition ; https://hal.inria.fr/hal-03373586 ; Cognition, Elsevier, 2021, 213, pp.104779. ⟨10.1016/j.cognition.2021.104779⟩ (2021)
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Vocal development in a large‐scale crosslinguistic corpus
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In: ISSN: 1363-755X ; EISSN: 1467-7687 ; Developmental Science ; https://hal.archives-ouvertes.fr/hal-03498978 ; Developmental Science, Wiley, 2021, 24 (5), ⟨10.1111/desc.13090⟩ (2021)
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Toward Cumulative Cognitive Science: A Comparison of Meta-Analysis, Mega-Analysis, and Hybrid Approaches
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In: EISSN: 2470-2986 ; Open Mind ; https://hal.archives-ouvertes.fr/hal-03498941 ; Open Mind, MIT Press, 2021, 5, pp.154-173. ⟨10.1162/opmi_a_00048⟩ (2021)
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Socioeconomic status correlates with measures of Language Environment Analysis (LENA) system: a meta-analysis
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In: ISSN: 0305-0009 ; EISSN: 1469-7602 ; Journal of Child Language ; https://hal.archives-ouvertes.fr/hal-03498959 ; Journal of Child Language, Cambridge University Press (CUP), In press, pp.1-15. ⟨10.1017/S0305000921000441⟩ (2021)
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The effect of Crianza Positiva e-messaging program on adult-child language interactions
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In: Behavioral Public Policy ; https://hal.archives-ouvertes.fr/hal-03498848 ; Behavioral Public Policy, 2021 (2021)
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Describing Vocalizations in Young Children: A Big Data Approach Through Citizen Science Annotation
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In: ISSN: 1092-4388 ; EISSN: 1558-9102 ; Journal of Speech, Language, and Hearing Research ; https://hal.archives-ouvertes.fr/hal-03498946 ; Journal of Speech, Language, and Hearing Research, American Speech-Language-Hearing Association, 2021, 64 (7), pp.2401-2416. ⟨10.1044/2021_JSLHR-20-00661⟩ (2021)
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Non-word repetition in bilingual children: the role of language exposure, vocabulary scores and environmental factors ...
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La ripetizione di non-parole in bambini bilingue, in funzione del loro vocabolario in italiano ...
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First DIHARD Challenge -- System Submissions and Scores ...
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First DIHARD Challenge -- System Submissions and Scores ...
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Learning and Processing Language from Wearables: Opportunities and Challenges ...
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Quantifying Sources of Variability in Infancy Research Using the Infant-Directed-Speech Preference
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A thorough evaluation of the Language Environment Analysis (LENA) system
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In: Behav Res Methods (2021)
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Abstract:
In the previous decade, dozens of studies involving thousands of children across several research disciplines have made use of a combined daylong audio-recorder and automated algorithmic analysis called the LENA® system, which aims to assess children’s language environment. While the system’s prevalence in the language acquisition domain is steadily growing, there are only scattered validation efforts on only some of its key characteristics. Here, we assess the LENA® system’s accuracy across all of its key measures: speaker classification, Child Vocalization Counts (CVC), Conversational Turn Counts (CTC), and Adult Word Counts (AWC). Our assessment is based on manual annotation of clips that have been randomly or periodically sampled out of daylong recordings, collected from (a) populations similar to the system’s original training data (North American English-learning children aged 3–36 months), (b) children learning another dialect of English (UK), and (c) slightly older children growing up in a different linguistic and socio-cultural setting (Tsimane’ learners in rural Bolivia). We find reasonably high accuracy in some measures (AWC, CVC), with more problematic levels of performance in others (CTC, precision of male adults and other children). Statistical analyses do not support the view that performance is worse for children who are dissimilar from the LENA® original training set. Whether LENA® results are accurate enough for a given research, educational, or clinical application depends largely on the specifics at hand. We therefore conclude with a set of recommendations to help researchers make this determination for their goals.
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Article
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URL: https://doi.org/10.3758/s13428-020-01393-5 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7855224/ http://www.ncbi.nlm.nih.gov/pubmed/32728916
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