Grammatical classification ("tagging") of words in language samples is a component of syntactic analysis for both clinical and research purposes. Previous studies have shown that probability-based software can be used to tag samples from adults and typically-developing children with high (about 95%) accuracy. The present study found that similar accuracy can be obtained in tagging samples from school-aged children with and without language impairment if the software uses tri-gram rather than bi-gram probabilities and large corpora are used to obtain probability information to train the tagging software.
College and Department
David O. McKay School of Education; Communication Disorders
BYU ScholarsArchive Citation
Millet, Deborah, "Automated Grammatical Tagging of Language Samples from Children with and without Language Impairment" (2003). All Theses and Dissertations. 1139.
automated grammatical tagging, grammatical classification, language samples, syntactic analysis, language impairment, DSS, developmental sentence scoring, Language Assessment, Remediation and Screening Procedure, LARSP, bi-gram probability, tri-gram probability