The Linearity of the Effect of Surprisal on Reading Times across Languages
Weijie Xu, Jason Sejin Chon, Tianran Liu, Richard Futrell
Abstract
In psycholinguistics, surprisal theory posits that the amount of online processing effort expended by a human comprehender per word positively correlates with the surprisal of that word given its preceding context. In addition to this overall correlation, more importantly, the specific quantitative form taken by the processing effort as a function of surprisal offers insights into the underlying cognitive mechanisms of language processing. Focusing on English, previous studies have looked into the linearity of surprisal on reading times. Here, we extend the investigation by examining eyetracking corpora of seven languages: Danish, Dutch, English, German, Japanese, Mandarin, and Russian. We find evidence for superlinearity in some languages, but the results are highly sensitive to which language model is used to estimate surprisal.
BibTeX
@inproceedings{
xu2023the,
title={The Linearity of the Effect of Surprisal on Reading Times across Languages},
author={Weijie Xu and Jason Sejin Chon and Tianran Liu and Richard Futrell},
booktitle={The 2023 Conference on Empirical Methods in Natural Language Processing},
year={2023},
url={https://openreview.net/forum?id=0SIyWZEOmJ}
}