Dyslexia Prediction from Natural Reading of Danish Texts

Marina Björnsdóttir, Nora Hollenstein, Maria Jung Barrett

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

Abstract

Dyslexia screening in adults is an open challenge since difficulties may not align with standardised tests designed for children. We collect eye-tracking data from natural reading of Danish texts from readers with dyslexia while closely following the experimental design of a corpus of readers without dyslexia. Research suggests that the opaque orthography of the Danish language affects the diagnostic characteristics of dyslexia. To the best of our knowledge, this is the first attempt to classify dyslexia from eye movements during reading in Danish. We experiment with various machine-learning methods, and our best model yields 0.85 F1 score.
OriginalsprogEngelsk
TitelProceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)
Antal sider11
Publikationsdato2023
Sider60-70
StatusUdgivet - 2023

Emneord

  • Dyslexia Screening
  • Adult Dyslexia
  • Eye-tracking
  • Natural Reading
  • Machine Learning

Fingeraftryk

Dyk ned i forskningsemnerne om 'Dyslexia Prediction from Natural Reading of Danish Texts'. Sammen danner de et unikt fingeraftryk.

Citationsformater