CMCL 2022 Shared Task on Multilingual and Crosslingual Prediction of Human Reading Behavior

Nora Hollenstein, Emmanuele Chersoni, Cassandra Jacobs, Yohei Oseki, Laurent Prévot, Enrico Santus


Abstract
We present the second shared task on eye-tracking data prediction of the Cognitive Modeling and Computational Linguistics Workshop (CMCL). Differently from the previous edition, participating teams are asked to predict eye-tracking features from multiple languages, including a surprise language for which there were no available training data. Moreover, the task also included the prediction of standard deviations of feature values in order to account for individual differences between readers.A total of six teams registered to the task. For the first subtask on multilingual prediction, the winning team proposed a regression model based on lexical features, while for the second subtask on cross-lingual prediction, the winning team used a hybrid model based on a multilingual transformer embeddings as well as statistical features.
Anthology ID:
2022.cmcl-1.14
Volume:
Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics
Month:
May
Year:
2022
Address:
Dublin, Ireland
Editors:
Emmanuele Chersoni, Nora Hollenstein, Cassandra Jacobs, Yohei Oseki, Laurent Prévot, Enrico Santus
Venue:
CMCL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
121–129
Language:
URL:
https://aclanthology.org/2022.cmcl-1.14
DOI:
10.18653/v1/2022.cmcl-1.14
Bibkey:
Cite (ACL):
Nora Hollenstein, Emmanuele Chersoni, Cassandra Jacobs, Yohei Oseki, Laurent Prévot, and Enrico Santus. 2022. CMCL 2022 Shared Task on Multilingual and Crosslingual Prediction of Human Reading Behavior. In Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics, pages 121–129, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
CMCL 2022 Shared Task on Multilingual and Crosslingual Prediction of Human Reading Behavior (Hollenstein et al., CMCL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.cmcl-1.14.pdf
Video:
 https://aclanthology.org/2022.cmcl-1.14.mp4