Syntactic complexity measures for detecting mild cognitive impairment

  • Authors:
  • Brian Roark;Margaret Mitchell;Kristy Hollingshead

  • Affiliations:
  • Oregon Health & Science University, Beaverton, Oregon;Oregon Health & Science University, Beaverton, Oregon;Oregon Health & Science University, Beaverton, Oregon

  • Venue:
  • BioNLP '07 Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing
  • Year:
  • 2007

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Abstract

We consider the diagnostic utility of various syntactic complexity measures when extracted from spoken language samples of healthy and cognitively impaired subjects. We examine measures calculated from manually built parse trees, as well as the same measures calculated from automatic parses. We show statistically significant differences between clinical subject groups for a number of syntactic complexity measures, and these differences are preserved with automatic parsing. Different measures show different patterns for our data set, indicating that using multiple, complementary measures is important for such an application.