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.- Anthology ID:
- 2023.findings-emnlp.1052
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2023
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Houda Bouamor, Juan Pino, Kalika Bali
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 15711–15721
- Language:
- URL:
- https://aclanthology.org/2023.findings-emnlp.1052
- DOI:
- 10.18653/v1/2023.findings-emnlp.1052
- Cite (ACL):
- Weijie Xu, Jason Chon, Tianran Liu, and Richard Futrell. 2023. The Linearity of the Effect of Surprisal on Reading Times across Languages. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 15711–15721, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- The Linearity of the Effect of Surprisal on Reading Times across Languages (Xu et al., Findings 2023)
- PDF:
- https://preview.aclanthology.org/ingest-2024-clasp/2023.findings-emnlp.1052.pdf