Abstract
Nilsson and Nivre (2009) introduced a tree-based model of persons' eye movements in reading. The individual variation between readers reportedly made application across readers impossible. While a tree-based model seems plausible for eye movements, we show that competitive results can be obtained with a linear CRF model. Increasing the inductive bias also makes learning across readers possible. In fact we observe next-to-no performance drop when evaluating models trained on gaze records of multiple readers on new readers.
Original language | English |
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Title of host publication | EMNLP 2013 |
Publisher | Association for Computational Linguistics |
Publication date | 2013 |
Pages | 803-807 |
ISBN (Electronic) | 978-1-937284-97-8 |
Publication status | Published - 2013 |