Estimation of english skill with a mobile eye tracker

Olivier Augereau, Hiroki Fujiyoshi, Kai Steven Kunze, Koichi Kise

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Learning a foreign language such as English is an importan task for many people. The process of learning take time and it is important to have a simple way to evaluate th progress of the skill. We propose a method to evaluate th reader's English skill based on a mobile eye tracking system The eye tracker captures the reader's behavior whil reading a document. The front camera of the eye tracke records the scene image that contains the read document By using a retrieval algorithm we can recognize the rea document and project the eye gaze data from the scene imag to the document space. Then, some features related t the reading and solving behavior on several documents ar computed. As a first result, we show that the TOEIC scor can be estimated with an error of 36.3 points.

Original languageEnglish
Title of host publicationUbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing
PublisherAssociation for Computing Machinery, Inc
Pages1777-1781
Number of pages5
ISBN (Electronic)9781450344623
DOIs
Publication statusPublished - 2016 Sep 12
Event2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016 - Heidelberg, Germany
Duration: 2016 Sep 122016 Sep 16

Other

Other2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016
CountryGermany
CityHeidelberg
Period16/9/1216/9/16

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Keywords

  • Eye tracking
  • Language estimation
  • LLAH

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software
  • Information Systems
  • Computer Networks and Communications
  • Human-Computer Interaction

Cite this

Augereau, O., Fujiyoshi, H., Kunze, K. S., & Kise, K. (2016). Estimation of english skill with a mobile eye tracker. In UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 1777-1781). Association for Computing Machinery, Inc. https://doi.org/10.1145/2968219.2968275