Using statistical parsing to detect agrammatic aphasia

Kathleen C. Fraser, Graeme Hirst, Jed A. Meltzer, Jennifer E. Mack, Cynthia K. Thompson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Agrammatic aphasia is a serious language impairment which can occur after a stroke or traumatic brain injury. We present an automatic method for analyzing aphasic speech using surface level parse features and context-free grammar production rules. Examining these features individually, we show that we can uncover many of the same characteristics of agrammatic language that have been reported in studies using manual analysis. When taken together, these parse features can be used to train a classifier to accurately predict whether or not an individual has aphasia. Furthermore, we find that the parse features can lead to higher classification accuracies than traditional measures of syntactic complexity. Finally, we find that a minimal amount of pre-processing can lead to better results than using either the raw data or highly processed data.

Original languageEnglish (US)
Title of host publicationACL 2014 - BioNLP 2014, Workshop on Biomedical Natural Language Processing, Proceedings of the Workshop
PublisherAssociation for Computational Linguistics (ACL)
Pages134-142
Number of pages9
ISBN (Electronic)9781941643181
StatePublished - 2014
EventACL 2014 Workshop on Biomedical Natural Language Processing, BioNLP 2014 - Baltimore, United States
Duration: Jun 27 2014Jun 28 2014

Publication series

NameProceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN (Print)0736-587X

Conference

ConferenceACL 2014 Workshop on Biomedical Natural Language Processing, BioNLP 2014
Country/TerritoryUnited States
CityBaltimore
Period6/27/146/28/14

Funding

This research was supported by the Natural Sciences and Engineering Research Council of Canada and National Institutes of Health R01DC01948 and R01DC008552.

ASJC Scopus subject areas

  • Computer Science Applications
  • Linguistics and Language
  • Language and Linguistics

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