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Liu, Houjun; MacWhinney, Brian; Fromm, Davida; Lanzi, Alyssa – Journal of Speech, Language, and Hearing Research, 2023
Purpose: A major barrier to the wider use of language sample analysis (LSA) is the fact that transcription is very time intensive. Methods that can reduce the required time and effort could help in promoting the use of LSA for clinical practice and research. Method: This article describes an automated pipeline, called Batchalign, that takes raw…
Descriptors: Automation, Language Tests, Computational Linguistics, Morphology (Languages)
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Dalton, Sarah Grace; Stark, Brielle C.; Fromm, Davida; Apple, Kristen; MacWhinney, Brian; Rensch, Amanda; Rowedder, Madyson – Journal of Speech, Language, and Hearing Research, 2022
Purpose: The aim of this study was to advance the use of structured, monologic discourse analysis by validating an automated scoring procedure for core lexicon (CoreLex) using transcripts. Method: Forty-nine transcripts from persons with aphasia and 48 transcripts from persons with no brain injury were retrieved from the AphasiaBank database. Five…
Descriptors: Validity, Discourse Analysis, Databases, Scoring
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Guo, Ling-Yu; Eisenberg, Sarita; Bernstein Ratner, Nan; MacWhinney, Brian – Language, Speech, and Hearing Services in Schools, 2018
Purpose: In this letter, the authors respond to Pavelko and Owens' (2017) newly advanced set of procedures for language sample analysis: Sampling Utterances and Grammatical Analysis Revised (SUGAR). Method: The authors contrast some of the new guidelines for transcription, morpheme segmentation, and language sample elicitation in SUGAR with…
Descriptors: Sampling, Grammar, Transcripts (Written Records), Morphemes