Paper: Using statistical parsing to detect agrammatic aphasia

ACL ID W14-3420
Title Using statistical parsing to detect agrammatic aphasia
Venue Proceedings of the BioNLP Shared Task 2013 Workshop
Session
Year 2014
Authors

Agrammatic aphasia is a serious language impairment which can occur after a stroke or traumatic brain injury. We present an automatic method for analyzing apha- sic speech using surface level parse fea- tures and context-free grammar produc- tion rules. Examining these features in- dividually, we show that we can uncover many of the same characteristics of agram- matic 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 classifica- tion accuracies than traditional measures of syntactic complexity. Finally, we find that a minimal amount of pre-processing can lead to better re...