mlsanityData to 14 Oct 2026

The Copenhagen Corpus of Eye Tracking Recordings from Natural Reading of Danish Texts

arXiv 2204.13311 ↗First posted 28 Apr 2022cs.CLcited by 7

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Abstract (arXiv)

Eye movement recordings from reading are one of the richest signals of human language processing. Corpora of eye movements during reading of contextualized running text is a way of making such records available for natural language processing purposes. Such corpora already exist in some languages. We present CopCo, the Copenhagen Corpus of eye tracking recordings from natural reading of Danish texts. It is the first eye tracking corpus of its kind for the Danish language. CopCo includes 1,832 sentences with 34,897 tokens of Danish text extracted from a collection of speech manuscripts. This first release of the corpus contains eye tracking data from 22 participants. It will be extended continuously with more participants and texts from other genres. We assess the data quality of the recorded eye movements and find that the extracted features are in line with related research. The dataset available here: https://osf.io/ud8s5/.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 9 of its 50 references that are in the map. First posted on arXiv 28 Apr 2022.

Builds on

9 of 50 references.

References · 9

  1. 2019ZuCo 2.0: A Dataset of Physiological Recordings During Natural Reading and Annotationcited by 66
  2. 2020Interpreting Attention Models with Human Visual Attention in Machine Reading Comprehensioncited by 29
  3. 2019Entity Recognition at First Sight: Improving NER with Eye Movement Informationcited by 26
  4. 2021Relative Importance in Sentence Processingcited by 22
  5. 2017Leveraging Cognitive Features for Sentiment Analysiscited by 19
  6. 2020Generating Image Descriptions via Sequential Cross-Modal Alignment Guided by Human Gazecited by 16
  7. 2021VQA-MHUG: A Gaze Dataset to Study Multimodal Neural Attention in Visual Question Answeringcited by 16
  8. 2021A Survey on Using Gaze Behaviour for Natural Language Processingcited by 11
  9. 2019Higher-order Comparisons of Sentence Encoder Representationscited by 10

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 2; 2025: 1; 2026: 3.

7 papers.