Abstract
Does the way a person read influence the way they understand information or is it the other way around? In regard to reading of English text, just how much we can learn from a person’s gaze pattern? It is known that while reading, we inadvertently form rational connections between pieces of information we pick up from the text. That reflects in certain disruptions in the norms of reading paradigm and that gives us clues to our interest level in reading activities.
In this paper, we validate the above statement and then propose a novel method of detecting the level of engagement in reading based on a person’s gaze-pattern. We organised some experiments in reading tasks of over thirty participants and the experimental outputs are classified with Artificial Neural Networks with an approximately 80 percent accuracy. The design of this approach is simple and computationally feasible enough to be applied in a real-life system.
“Your eyes are the windows to your soul”
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Zhu, D., Gedeon, T., Taylor, K.: Keyboard before Head Tracking Depresses User Success in Remote Camera Control. In: Gross, T., Gulliksen, J., Kotzé, P., Oestreicher, L., Palanque, P., Prates, R.O., Winckler, M. (eds.) INTERACT 2009. LNCS, vol. 5727, pp. 319–331. Springer, Heidelberg (2009)
Zhu, D., Mendis, B.S., Gedeon, T., Asthana, A., Goecke, R.: A Hybrid Fuzzy Approach for Human Eye Gaze Pattern Recognition. In: Köppen, M., Kasabov, N., Coghill, G. (eds.) ICONIP 2008. LNCS, vol. 5507, pp. 655–662. Springer, Heidelberg (2009)
Fahey, D.: A Preliminary Investigation into using Eye-Tracking to Analyse a Persons Reading Behaviour. B.S. thesis. The School of Computer Science Australian National University (2009)
Byvatov, E., Fechner, U., Sadowski, J., Schneider, G.: Comparison of Support Vector Machine and Artificial Neural Network Systems for Drug/Nondrug Classification. Journal of Chemical Information and Computer Sciences, 1882–1889 (2003)
Hagan, M.T., Menhaj, M.B.: Training feedforward networks with the Marquardt algorithm. IEEE Transactions on Neural Networks 5(6), 989–993 (1994), doi:10.1109/72.329697
Miller, G.A.: The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information. In: The Psychology of Communication: Seven Essays. Penguin Books, Inc. (1970)
Mendis, B.S.U., Gedeon, T.D., Koczy, L.T.: Learning Generalized Weighted Relevance Aggregation Operators Using Levenberg-Marquardt Method. In: International Conference on Hybrid Intelligent Systems (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Vo, T., Mendis, B.S.U., Gedeon, T. (2010). Gaze Pattern and Reading Comprehension. In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds) Neural Information Processing. Models and Applications. ICONIP 2010. Lecture Notes in Computer Science, vol 6444. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17534-3_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-17534-3_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17533-6
Online ISBN: 978-3-642-17534-3
eBook Packages: Computer ScienceComputer Science (R0)