We present a novel reading comprehension eye tracking dataset - MQA-RC - which allows researchers to observe changes in reading behavior in three comprehension tasks. Our extension uses 32 movie plots, with corresponding question-answer (QA) pairs, from the benchmark MovieQA dataset (Tapaswi et al., 2015). To the best of our knowledge, this is the first eye tracking dataset over a QA corpus and thus provides a gold standard to compare and synchronize model versus human visual attention in machine comprehension tasks.
The full dataset can be requested by contacting us and filling out a license agreement.
Contact: Ekta Sood,
The data is only to be used for non-commercial scientific purposes. If you use this dataset in a scientific publication, please cite the following paper:
Interpreting Attention Models with Human Visual Attention in Machine Reading Comprehension
Proc. ACL SIGNLL Conference on Computational Natural Language Learning (CoNLL),