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Abstract:
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One of the aims of the Eye-to-IT project is to investigate the possibility of
using eye-tracking devices for detecting situations of targeted help for human
translators. A prerequisite for automated assistance in human translation is
the understanding and modelling of reading behaviour, the ability to follow
human eye movements and to map gaze sample points — the output of eyetracking
devices — onto words and symbols fixated.
Within the Eye-to-IT project we currently use a so-called “Gaze-to-
Word Mapping” (GWM) device (ˇSpakov 2008) that first computes possible
fixations from sequences of gaze sample coordinates and then maps the fixations
on the words which are likely to be fixated.
This paper suggests an alternative framework of a probabilistic gaze
mapping model for reading, in which fixations on textual objects are directly
computed from the gaze sample points. The framework integrates various
knowledge sources with the aim to compute the most likely fixations on words
and symbols on the basis of the available data. |
This work is licensed under a Creative Commons License.
