Analysis of Time-Series Eye-Tracking Data to Classify and Quantify Reading Ability

Abstract

Time series eye-tracking data, consisting of a sequence of fixations and saccades is a rich source of information for research in the area of cognitive neuroscience. With advanced eye-tracking equipments, many aspects of human perception and cognition are now analyzed from fixations and saccades data. Reading is a complex cognitive process involving a coordination of eye movements on the text and its comprehension. Reading necessitates both a vocabulary sufficient to cover the words in the text, as well as the ability to comprehend the syntax and composition of complex sentences therein. For rapid reading additional factors are involved, like a better peripheral vision. The motivation of this work is to pinpoint lacunae in reading, from her/his eye-tracking data while reading—whether the person lacks in vocabulary, or can not comprehend complex sentences, or needs scanning the text letter by letter which makes the reading very slow. Once the problem for an individual is identified, suggestions to improve reading ability could be made. We also investigated whether there is any basic difference how a native language (L1) and a second language (L2) are read? Is there any difference while reading a text in phonetic script and in logosyllabic script? Eye tracking data was collected while subjects were asked to read texts in their native language (L1) as well as in their second language (L2). Time series data of horizontal axis position and vertical axis position of the location where the fovea is focused, were collected. Simple features were extracted for analysis. For experiments with second language (in this work it is English) subjects belonged to 3 groups: expert, medium proficiency and poor in English. We proposed a formula to evaluate the reading ability, and compared scores with what they obtained in standardized English language test like TOEFL or TOEIC. We also find the correlation of a person’s ability of peripheral vision (by Schultz’s test) and reading speed. The final goal of this work is to build a platform for e-learning of foreign language, while eye-tracking data is analyzed in real-time and appropriate suggestions extended.