Recognizing Personal Characteristics of Readers using Eye-Movements and Text Features
Pascual Mart'inez-GÃ mez, Tadayoshi Hara, Akiko Aizawa · International Conference on Computational Linguistics · 2012
In the present work we raise the hypothesis that eye-movements when reading texts reveal task performance, as measured by the level of understanding of the reader. With the objective of testing that hypothesis, we introduce a framework to integrate geometric information of eye-movements and text layout into natural language processing models via image processing techniques. We evidence the patterns in reading behavior between subjects with similar task performance using principal component analysis and quantify the likelihood of our hypothesis using the concept of linear separability. Finally, we point to potential applications that could benefit from these findings.