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.
| Original language | English |
|---|---|
| Title of host publication | CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop |
| Editors | Emmanuele Chersoni, Nora Hollenstein, Cassandra L. Jacobs, Yohei Oseki, Laurent Prevot, Enrico Santus |
| Publisher | Association for Computational Linguistics (ACL) |
| Pages | 108-113 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781955917292 |
| DOIs | |
| Publication status | Published - 31 Dec 2022 |
| Event | 12th Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2022 - Dublin, Ireland Duration: 26 May 2022 → … |
Publication series
| Name | CMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop |
|---|
Conference
| Conference | 12th Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2022 |
|---|---|
| Country/Territory | Ireland |
| City | Dublin |
| Period | 26/05/22 → … |
Bibliographical note
Publisher Copyright:© 2022 Association for Computational Linguistics.
ASJC Scopus subject areas
- Language and Linguistics
- Artificial Intelligence
- Software
- Linguistics and Language
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