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The ZuCo benchmark on cross-subject reading task classification with EEG and eye-tracking data


Hollenstein, Nora; Tröndle, Marius; Plomecka, Martyna; Kiegeland, Samuel; Özyurt, Yilmazcan; Jäger, Lena A; Langer, Nicolas (2023). The ZuCo benchmark on cross-subject reading task classification with EEG and eye-tracking data. Frontiers in Psychology, 13:1028824.

Abstract

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 natural reading of English sentences. The training dataset is publicly available, and we present a newly recorded hidden testset. We provide multiple solid baseline methods for this task and discuss future improvements. We release our code and provide an easy-to-use interface to evaluate new approaches with an accompanying public leaderboard: www.zuco-benchmark.com.

Abstract

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 natural reading of English sentences. The training dataset is publicly available, and we present a newly recorded hidden testset. We provide multiple solid baseline methods for this task and discuss future improvements. We release our code and provide an easy-to-use interface to evaluate new approaches with an accompanying public leaderboard: www.zuco-benchmark.com.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Psychology
06 Faculty of Arts > Institute of Computational Linguistics
06 Faculty of Arts > Zurich Center for Linguistics
08 Research Priority Programs > Digital Society Initiative
Dewey Decimal Classification:410 Linguistics
000 Computer science, knowledge & systems
Uncontrolled Keywords:General Psychology
Language:English
Date:12 January 2023
Deposited On:17 Jan 2024 15:31
Last Modified:31 Mar 2024 01:37
Publisher:Frontiers Research Foundation
ISSN:1664-1078
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.3389/fpsyg.2022.1028824
Related URLs:https://www.zora.uzh.ch/id/eprint/229121/
https://doi.org/10.1101/2022.03.08.483414
PubMed ID:36710838
  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)