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Accuracy of Automated Grammatical Tagging of Narrative Language Samples from Spanish-Speaking Children

The present study measured the accuracy of automated grammatical tagging software as compared to manual tagging in Spanish-speaking children's personal and fictional event narrative language samples. Studies have identified articles, clitic (contracted with a verb) pronouns, and verbs as clinical markers for language impairment in Spanish-speaking children. Automated grammatical tagging software may aid in the rapid identification of these grammatical markers. Grammatical morphemes of 30 first and fourth grade children's personal and fictional event narrative samples were tagged and compared with their respective manually tagged samples. The accuracy of word-level coding averaged 91%, and similar accuracy was found for clinically significant tags. Automated grammatical analysis has the potential to accurately identify clinically relevant grammatical forms in samples from children who speak Spanish.

Identiferoai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-3983
Date08 March 2012
CreatorsHarmon, Tyson Gordon
PublisherBYU ScholarsArchive
Source SetsBrigham Young University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations
Rightshttp://lib.byu.edu/about/copyright/

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