  Gaze behaviour has been used as a way to gather cognitive information for a
number of years. In this paper, we discuss the use of gaze behaviour in solving
different tasks in natural language processing (NLP) without having to record
it at test time. This is because the collection of gaze behaviour is a costly
task, both in terms of time and money. Hence, in this paper, we focus on
research done to alleviate the need for recording gaze behaviour at run time.
We also mention different eye tracking corpora in multiple languages, which are
currently available and can be used in natural language processing. We conclude
our paper by discussing applications in a domain - education - and how learning
gaze behaviour can help in solving the tasks of complex word identification and
automatic essay grading.
