Publication: The ZuCo Benchmark on Cross-Subject Reading Task Classification with EEG and Eye-Tracking Data
The ZuCo Benchmark on Cross-Subject Reading Task Classification with EEG and Eye-Tracking Data
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Hollenstein, N., Tröndle, M., Plomecka, M., Kiegeland, S., Özyurt, Y., Jäger, L. A., & Langer, N. (2022). The ZuCo Benchmark on Cross-Subject Reading Task Classification with EEG and Eye-Tracking Data (No. 483414; BioRxiv). https://doi.org/10.1101/2022.03.08.483414
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We present a new machine learning benchmark for reading task classification with the goal of advancing EEG and eye-tracking research at the intersection between computational language processing and cognitive neuroscience. The benchmark task consists of a cross-subject classification to distinguish between two reading paradigms: normal reading and task-specific reading. The data for the benchmark is based on the Zurich Cognitive Language Processing Corpus (ZuCo 2.0), which provides simultaneous eye-tracking and EEG signals from natura
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Hollenstein, N., Tröndle, M., Plomecka, M., Kiegeland, S., Özyurt, Y., Jäger, L. A., & Langer, N. (2022). The ZuCo Benchmark on Cross-Subject Reading Task Classification with EEG and Eye-Tracking Data (No. 483414; BioRxiv). https://doi.org/10.1101/2022.03.08.483414
