Reading Between the Lines: A dataset and a study on why some texts are tougher than others
Khallaf, Nouran, Eugeni, Carlo, Sharoff, Serge
–arXiv.org Artificial Intelligence
Our research aims at better understanding what makes a text difficult to read for specific audiences with intellectual disabilities, more specifically, people who have limitations in cognitive functioning, such as reading and understanding skills, an IQ below 70, and challenges in conceptual domains. We introduce a scheme for the annotation of difficulties which is based on empirical research in psychology as well as on research in translation studies. The paper describes the annotated dataset, primarily derived from the parallel texts (standard English and Easy to Read English translations) made available online. we fine-tuned four different pre-trained transformer models to perform the task of multiclass classification to predict the strategies required for simplification. We also investigate the possibility to interpret the decisions of this language model when it is aimed at predicting the difficulty of sentences. The resources are available from https://github.com/Nouran-Khallaf/why-tough
arXiv.org Artificial Intelligence
Jan-3-2025
- Country:
- Asia
- Middle East > UAE
- Abu Dhabi Emirate > Abu Dhabi (0.04)
- Singapore (0.04)
- Middle East > UAE
- Europe
- Belgium > Brussels-Capital Region
- Brussels (0.04)
- Finland > Southwest Finland
- Turku (0.04)
- Netherlands > North Holland
- Amsterdam (0.04)
- Romania > Vest Development Region
- Timiș County > Timișoara (0.04)
- United Kingdom
- England > West Yorkshire
- Leeds (0.04)
- Scotland (0.05)
- England > West Yorkshire
- Belgium > Brussels-Capital Region
- North America > United States
- New York (0.04)
- Asia
- Genre:
- Research Report > New Finding (0.68)
- Industry:
- Technology: