Publication: Reading Task Classification Using EEG and Eye-Tracking Data
Reading Task Classification Using EEG and Eye-Tracking Data
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Hollenstein, N., Tröndle, M., Plomecka, M., Kiegeland, S., Özyurt, Y., Jäger, L. A., & Langer, N. (2021). Reading Task Classification Using EEG and Eye-Tracking Data (2112.0631; ArXiv.Org). https://arxiv.org/abs/2112.06310
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The Zurich Cognitive Language Processing Corpus (ZuCo) provides eye-tracking and EEG signals from two reading paradigms, normal reading and task-specific reading. We analyze whether machine learning methods are able to classify these two tasks using eye-tracking and EEG features. We implement models with aggregated sentence-level features as well as fine-grained word-level features. We test the models in within-subject and cross-subject evaluation scenarios. All models are tested on the ZuCo 1.0 and ZuCo 2.0 data subsets, which are ch
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Hollenstein, N., Tröndle, M., Plomecka, M., Kiegeland, S., Özyurt, Y., Jäger, L. A., & Langer, N. (2021). Reading Task Classification Using EEG and Eye-Tracking Data (2112.0631; ArXiv.Org). https://arxiv.org/abs/2112.06310
