LangResearchLab_NC at CMCL2021 Shared Task: Predicting Gaze Behaviour Using Linguistic Features and Tree Regressors
Raksha Agarwal, Niladri Chatterjee · 2021
Analysis of gaze data behaviour has gained momentum in recent years for different NLP applications.The present paper aims at modelling gaze data behaviour of tokens in the context of a sentence.We have experimented with various Machine Learning Regression Algorithms on a feature space comprising the linguistic features of the target tokens for prediction of five Eye-Tracking features.CatBoost Regressor performed the best and achieved fourth position in terms of MAE based accuracy measurement for the ZuCo Dataset.