Abstract
In this paper, we present a unified model that works for both multilingual and crosslingual prediction of reading times of words in various languages. The secret behind the success of this model is in the preprocessing step where all words are transformed to their universal language representation via the International Phonetic Alphabet (IPA). To the best of our knowledge, this is the first study to favorably exploit this phonological property of language for the two tasks. Various feature types were extracted covering basic frequencies, n-grams, information theoretic, and psycholinguistically-motivated predictors for model training. A finetuned Random Forest model obtained best performance for both tasks with 3.8031 and 3.9065 MAE scores for mean first fixation duration (FFDAvg) and mean total reading time (TRTAvg) respectively.- Anthology ID:
- 2022.cmcl-1.12
- Original:
- 2022.cmcl-1.12v1
- Version 2:
- 2022.cmcl-1.12v2
- Volume:
- Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics
- Month:
- May
- Year:
- 2022
- Address:
- Dublin, Ireland
- Venue:
- CMCL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 108–113
- Language:
- URL:
- https://aclanthology.org/2022.cmcl-1.12
- DOI:
- 10.18653/v1/2022.cmcl-1.12
- Cite (ACL):
- Joseph Marvin Imperial. 2022. NU HLT at CMCL 2022 Shared Task: Multilingual and Crosslingual Prediction of Human Reading Behavior in Universal Language Space. In Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics, pages 108–113, Dublin, Ireland. Association for Computational Linguistics.
- Cite (Informal):
- NU HLT at CMCL 2022 Shared Task: Multilingual and Crosslingual Prediction of Human Reading Behavior in Universal Language Space (Imperial, CMCL 2022)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2022.cmcl-1.12.pdf
- Code
- imperialite/cmcl2022-unified-eye-tracking-ipa