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Gaze Pattern and Reading Comprehension

Vo, Tan; Mendis, B Sumudu; Gedeon, Tamas (Tom)

Description

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...[Show more]

dc.contributor.authorVo, Tan
dc.contributor.authorMendis, B Sumudu
dc.contributor.authorGedeon, Tamas (Tom)
dc.coverage.spatialSydney Australia
dc.date.accessioned2015-12-10T22:30:23Z
dc.date.createdNovember 22-25 2010
dc.identifier.isbn9783642175336
dc.identifier.urihttp://hdl.handle.net/1885/55070
dc.description.abstractDoes 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".
dc.publisherSpringer
dc.relation.ispartofseriesInternational Conference on Neural Information Processing (ICONIP 2010)
dc.sourceProceedings of the International Conference on Neural Information Processing (ICONIP 2010)
dc.subjectKeywords: Artificial Neural Network; Eye-gaze; Grid-based clustering; Interest level; Novel methods; Reading comprehension; Real-life systems; SVM; Data processing; Neural networks Artificial Neural Network; Eye-gaze Pattern; Grid-based Clustering; SVM
dc.titleGaze Pattern and Reading Comprehension
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2010
local.identifier.absfor080107 - Natural Language Processing
local.identifier.ariespublicationU3594520xPUB318
local.type.statusPublished Version
local.contributor.affiliationVo, Tan, College of Engineering and Computer Science, ANU
local.contributor.affiliationMendis, B Sumudu, College of Engineering and Computer Science, ANU
local.contributor.affiliationGedeon, Tamas (Tom), College of Engineering and Computer Science, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.startpage124
local.bibliographicCitation.lastpage131
local.identifier.doi10.1007/978-3-642-17534-3_16
local.identifier.absseo970108 - Expanding Knowledge in the Information and Computing Sciences
dc.date.updated2016-02-24T10:17:56Z
local.identifier.scopusID2-s2.0-78650218400
CollectionsANU Research Publications

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