A Dataset of Underrepresented Languages in Eye Tracking Research

Abstract

A number of factors come together to limit the diversity of eye-tracking research, where the majority of papers are conducted with stimuli in the English language. Studying eye movement over other languages is important considering that each language provides unique insights into human cognition. Recently, there have been valued efforts to present datasets from other languages, yet these efforts focused mostly on European languages. In this paper we highlight issues that limit diversity in eye tracking research on reading, and we present our work in collecting an open-access multilingual reading dataset of underrepresented languages. Utilizing a high-frequency research eye tracker (EyeLink 1000 Plus), we record eye tracking data of native and second language readers of English, Spanish, Chinese, Hindi, Russian, Arabic, Japanese, Kazakh, Urdu, and Vietnamese. The dataset includes demographics, language proficiency self-reporting, and answers to comprehension questions. The current version of the dataset, which we make publicly available, consists of 97 trials by 40 participants. With the goal of increasing the number of participants and included languages, we aim to make studying underrepresented languages more accessible to researchers and tool makers.