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GECO-CN : Ghent Eye-tracking COrpus of sentence reading for Chinese-English bilinguals Universiteit Gent
The current work presents the very first eye-tracking corpus of natural reading by Chinese-English bilinguals, whose two languages entail different writing systems and orthographies. Participants read an entire novel in these two languages, presented in paragraphs on screen. Half of the participants first read half of the novel in their native language (Simplified Chinese) and then the rest of the novel in their second language (English), while ...
How do learners use a CALL environment? An eye-tracking study Universiteit Gent KU Leuven
This study investigates how learners use a freely available web-based multimodal language learning environment based on videos and newspaper articles with corresponding exercises and learning support in the form of help options, NedBox, for learning L2 Dutch. In order to measure learners’ use, a combination of eye movement and screen recording data were analysed. The study also examines how learners’ eye movements and use of the environment are ...
The processing of native advertising compared to banner advertising : an eye-tracking experiment Universiteit Gent Universiteit Antwerpen KU Leuven
This paper aims to better understand the effect of visual attention on the processing of banner and native advertisements on Facebook and consequently on brand recognition and brand attitude. Using an eye-tracking experiment (N = 90), we show that a native advertisement attracts more and longer visual attention (i.e., total fixation duration, fixation count, and average visit duration) compared to a banner advertisement. Moreover, we show that ...
GECO-MT : the Ghent Eye-tracking Corpus of Machine Translation Universiteit Gent
In the present paper, we describe a large corpus of eye movement data, collected during natural reading of a human translation and a machine translation of a full novel. This data set, called GECO-MT (Ghent Eye-tracking Corpus of Machine Translation) expands upon an earlier corpus called GECO (Ghent Eye-tracking Corpus) by Cop et al. (2017). The eye movement data in GECO-MT will be used in future research to investigate the effect of machine ...
Anticipation and timing of turn-taking in dialogue interpreting : a quantitative study using mobile eye-tracking data Universiteit Gent KU Leuven
It's all in the eyes : using eye-tracking to assess the readability of machine translated literature Universiteit Gent
With the arrival of neural machine translation (NMT) systems, translation quality has improved enormously. Despite these quality improvements, especially for more creative text types such as literary texts, remarkable differences can be observed when comparing human and machine translations. Webster et al. (2020) compared the modern Dutch human translations of four classic novels with their machine translated versions generated by Google ...