In 2024, MultiplEYE’s network members have continued to foster funding support to shape the digital transformation of society through eye-tracking. Check the list of projects funded during 2024, showcasing MultiplEYE’s dedication to advancing research in various subfields of linguistics.
Check out MultiplEYE scientific publications comming out from collaborations between MultiplEYE network members from January to July 2024.
Maja Stegenwallner-Schütz is currently a guest professor at the Institute of Rehabilitation Science at the Humboldt-University of Berlin. She contributes to the development and validation of the reading comprehension stimuli of the MultiplEYE data collection and oversees the translation process. She also participated in the selection of psychometric tests as well as in the development…
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The MultiplEYE COST Action aims to foster an interdisciplinary network of research groups working on collecting eye tracking data from reading in many languages. The goal is to support the development of a large multilingual eye tracking corpus and enable researchers to collect data by sharing infrastructure and their knowledge between various fields, including linguistics, psychology, and computer science. This data collection can then be used to study human language processing from a psycholinguistic perspective as well as to improve and evaluate computational language processing from a machine learning perspective.
The MultiplEYE COST Action has three core goals:
1. To provide a platform for discussing the desiderata and reaching a common ground between psycholinguists and computational linguists for a multilingual eye-tracking and self-paced reading data collection. This includes developing and reaching a consensus concerning experiment design, stimulus selection, stimulus layout, experimental procedure, and data preprocessing.
2. To enable discussions on the psycholinguistic research questions that can be addressed with multilingual eye movement data and providing a broad network to initiate collaborations focusing on cross-linguistic and multilingual projects.
3. To advance the natural language processing and machine learning applications that leverage eye-tracking data and improve their cross-linguistic generalization abilities by bringing researchers from psycholinguistics and computational linguistics closer together.