The eye as the window of the language ability: Estimation of English skills by analyzing eye movement while reading documents

Reading-life log is a research field of analyzing our activities of reading documents to know more about readers and documents. In this paper we propose an implementation of reading-life log which is to estimate the English language skill by analyzing the activities of reading English documents. As input for the analysis, we employ eye movement information, because we consider the eye movement of skillful readers is far different from that of novices. From the experiments, we have found that the following two features are informative: (1) the sum of fixation duration, and (2) the sum of the velocity of saccades. By using these features the proposed method is to estimate the class of English skill from among low, middle and high, which are defined based on the scores of English standardized test called TOEIC. From the experimental results with 11 subjects and 10 documents, we have been successful to estimate the class with the accuracy of 90.9%.

[1]  Andreas Dengel,et al.  A robust realtime reading-skimming classifier , 2012, ETRA.

[2]  Kai Kunze,et al.  Towards inferring language expertise using eye tracking , 2013, CHI Extended Abstracts.

[3]  D. E. Irwin Fixation location and fixation duration as indices of cognitive processing , 2004 .

[4]  Gerhard Tröster,et al.  Eye Movement Analysis for Activity Recognition Using Electrooculography , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Robert J Barry,et al.  EEG Analysis of Children with Attention-Deficit/Hyperactivity Disorder and Comorbid Reading Disabilities , 2002, Journal of learning disabilities.

[6]  Pascual Martínez-Gómez,et al.  Recognition of understanding level and language skill using measurements of reading behavior , 2014, IUI.

[7]  Rong Huang,et al.  The Reading-Life Log -- Technologies to Recognize Texts That We Read , 2013, 2013 12th International Conference on Document Analysis and Recognition.

[8]  Donna Christian,et al.  English Language Learners in U.S. Schools: An Overview of Research Findings , 2005 .

[9]  M. Just,et al.  The psychology of reading and language comprehension , 1986 .

[10]  Andreas Bulling,et al.  Cognition-Aware Computing , 2014, IEEE Pervasive Computing.

[11]  George D. Spaghe Is This a Breakthrough in Reading , 2016 .

[12]  Kai Kunze,et al.  The Wordometer -- Estimating the Number of Words Read Using Document Image Retrieval and Mobile Eye Tracking , 2013, 2013 12th International Conference on Document Analysis and Recognition.

[13]  Joseph K. Torgesen,et al.  Repeated reading and reading fluency in learning disabled children. , 1985 .

[14]  Ralf Engbert,et al.  Tracking the mind during reading: the influence of past, present, and future words on fixation durations. , 2006, Journal of experimental psychology. General.

[15]  Hao Jiang,et al.  User-oriented document summarization through vision-based eye-tracking , 2009, IUI.

[16]  Hans-Werner Gellersen,et al.  Multimodal recognition of reading activity in transit using body-worn sensors , 2012, TAP.

[17]  Gerhard Tröster,et al.  Eye Movement Analysis for Activity Recognition Using Electrooculography , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  Andreas Dengel,et al.  Text 2.0 , 2010, CHI EA '10.

[19]  Kai Kunze,et al.  I know what you are reading: recognition of document types using mobile eye tracking , 2013, ISWC '13.

[20]  Andreas Dengel,et al.  Towards robust gaze-based objective quality measures for text , 2012, ETRA '12.

[21]  Evelyn C. Ferstl,et al.  The extended language network: A meta‐analysis of neuroimaging studies on text comprehension , 2008, Human brain mapping.

[22]  K. Rayner The 35th Sir Frederick Bartlett Lecture: Eye movements and attention in reading, scene perception, and visual search , 2009, Quarterly journal of experimental psychology.