Target word prediction and paraphasia classification in spoken discourse

Joel Adams, Steven Bedrick, Gerasimos Fergadiotis, Kyle Gorman, Jan Van Santen

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

Abstract

We present a system for automatically detecting and classifying phonologically anomalous productions in the speech of individuals with aphasia. Working from transcribed discourse samples, our system identifies neologisms, and uses a combination of string alignment and language models to produce a lattice of plausible words that the speaker may have intended to produce. We then score this lattice according to various features, and attempt to determine whether the anomalous production represented a phonemic error or a genuine neologism. This approach has the potential to be expanded to consider other types of paraphasic errors, and could be applied to a wide variety of screening and therapeutic applications.

Original languageEnglish (US)
Title of host publicationBioNLP 2017 - SIGBioMed Workshop on Biomedical Natural Language Processing, Proceedings of the 16th BioNLP Workshop
PublisherAssociation for Computational Linguistics (ACL)
Pages1-8
Number of pages8
ISBN (Electronic)9781945626593
StatePublished - 2017
Event16th SIGBioMed Workshop on Biomedical Natural Language Processing, BioNLP 2017 - Vancouver, Canada
Duration: Aug 4 2017 → …

Publication series

NameBioNLP 2017 - SIGBioMed Workshop on Biomedical Natural Language Processing, Proceedings of the 16th BioNLP Workshop

Conference

Conference16th SIGBioMed Workshop on Biomedical Natural Language Processing, BioNLP 2017
Country/TerritoryCanada
CityVancouver
Period8/4/17 → …

ASJC Scopus subject areas

  • Language and Linguistics
  • Computer Science Applications
  • Information Systems
  • Software
  • Biomedical Engineering
  • Health Informatics

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