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McDonald, Margarethe; Kwon, Taeahn; Kim, Hyunji; Lee, Youngki; Ko, Eon-Suk – Journal of Speech, Language, and Hearing Research, 2021
Purpose: The algorithm of the Language ENvironment Analysis (LENA) system for calculating language environment measures was trained on American English; thus, its validity with other languages cannot be assumed. This article evaluates the accuracy of the LENA system applied to Korean. Method: We sampled sixty 5-min recording clips involving 38 key…
Descriptors: Computational Linguistics, Korean, Audio Equipment, Accuracy
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Cristia, Alejandrina; Bulgarelli, Federica; Bergelson, Elika – Journal of Speech, Language, and Hearing Research, 2020
Purpose: The Language Environment Analysis (LENA) system provides automated measures facilitating clinical and nonclinical research and interventions on language development, but there are only a few, scattered independent reports of these measures' validity. The objectives of the current systematic review were to (a) discover studies comparing…
Descriptors: Intervention, Measures (Individuals), Language Acquisition, Accuracy
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Utianski, Rene L.; Martin, Peter R.; Hanley, Holly; Duffy, Joseph R.; Botha, Hugo; Clark, Heather M.; Whitwell, Jennifer L.; Josephs, Keith A. – Journal of Speech, Language, and Hearing Research, 2021
Purpose: Individuals with primary progressive apraxia of speech (PPAOS) have apraxia of speech (AOS) in which disruptions in articulation or prosody predominate the speech pattern, referred to, respectively, as phonetic or prosodic subtypes. Many develop aphasia and/or dysarthria. Past research has demonstrated that simple temporal acoustic…
Descriptors: Speech Communication, Longitudinal Studies, Articulation (Speech), Intonation
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Jiao, Yishan; LaCross, Amy; Berisha, Visar; Liss, Julie – Journal of Speech, Language, and Hearing Research, 2019
Purpose: Subjective speech intelligibility assessment is often preferred over more objective approaches that rely on transcript scoring. This is, in part, because of the intensive manual labor associated with extracting objective metrics from transcribed speech. In this study, we propose an automated approach for scoring transcripts that provides…
Descriptors: Suprasegmentals, Phonemes, Error Patterns, Scoring