Dyslexia Prediction from Natural Reading of Danish Texts
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.- Anthology ID:
- 2023.nodalida-1.7
- Volume:
- Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)
- Month:
- May
- Year:
- 2023
- Address:
- Tórshavn, Faroe Islands
- Editors:
- Tanel Alumäe, Mark Fishel
- Venue:
- NoDaLiDa
- SIG:
- Publisher:
- University of Tartu Library
- Note:
- Pages:
- 60–70
- Language:
- URL:
- https://aclanthology.org/2023.nodalida-1.7
- DOI:
- Cite (ACL):
- Marina Björnsdóttir, Nora Hollenstein, and Maria Barrett. 2023. Dyslexia Prediction from Natural Reading of Danish Texts. In Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa), pages 60–70, Tórshavn, Faroe Islands. University of Tartu Library.
- Cite (Informal):
- Dyslexia Prediction from Natural Reading of Danish Texts (Björnsdóttir et al., NoDaLiDa 2023)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/2023.nodalida-1.7.pdf