Patterns of Text Readability in Human and Predicted Eye Movements
Nora Hollenstein, Itziar González-Dios, Lisa Beinborn, Lena A. Jäger · 2022
It has been shown that multilingual transformer models are able to predict human reading behavior when fine-tuned on small amounts of eye tracking data.As the cumulated prediction results do not provide insights into the linguistic cues that the model acquires to predict reading behavior, we conduct a deeper analysis of the predictions from the perspective of readability.We try to disentangle the three-fold relationship between human eye movements, the capability of language models to predict these eye movement patterns, and sentencelevel readability measures for English.We compare a range of model configurations to multiple baselines.We show that the models exhibit difficulties with function words and that pre-training only provides limited advantages for linguistic generalization.