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Your search keyword '"Berzak, Yevgeni"' showing total 13 results
Start Over Author "Berzak, Yevgeni" Publisher association for computational linguistics
13 results on '"Berzak, Yevgeni"'

2. Predicting Text Readability from Scrolling Interactions

Author

Gooding, Sian, Berzak, Yevgeni, Mak, Tony, and Sharifi, Matt

Subjects
FOS: Computer and information sciences, Computer Science - Computation and Language, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, Computer Science - Human-Computer Interaction, Computation and Language (cs.CL), Human-Computer Interaction (cs.HC)
Abstract

Judging the readability of text has many important applications, for instance when performing text simplification or when sourcing reading material for language learners. In this paper, we present a 518 participant study which investigates how scrolling behaviour relates to the readability of a text. We make our dataset publicly available and show that (1) there are statistically significant differences in the way readers interact with text depending on the text level, (2) such measures can be used to predict the readability of text, and (3) the background of a reader impacts their reading interactions and the factors contributing to text difficulty.

Published
2021
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3. Assessing Language Proficiency from Eye Movements in Reading

Author

Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences, Berzak, Yevgeni, Katz, Boris, Levy, Roger P, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences, Berzak, Yevgeni, Katz, Boris, and Levy, Roger P

Abstract

We present a novel approach for determining learners' second language proficiency which utilizes behavioral traces of eye movements during reading. Our approach provides standalone eyetracking based English proficiency scores which reflect the extent to which the learner's gaze patterns in reading are similar to those of native English speakers. We show that our scores correlate strongly with standardized English proficiency tests. We also demonstrate that gaze information can be used to accurately predict the outcomes of such tests. Our approach yields the strongest performance when the test taker is presented with a suite of sentences for which we have eyetracking data from other readers. However, it remains effective even using eyetracking with sentences for which eye movement data have not been previously collected. By deriving proficiency as an automatic byproduct of eye movements during ordinary reading, our approach offers a potentially valuable new tool for second language proficiency assessment. More broadly, our results open the door to future methods for inferring reader characteristics from the behavioral traces of reading.

Published
2021

10. Universal Dependencies for Learner English

Author

Berzak, Yevgeni, primary, Kenney, Jessica, additional, Spadine, Carolyn, additional, Wang, Jing Xian, additional, Lam, Lucia, additional, Mori, Keiko Sophie, additional, Garza, Sebastian, additional, and Katz, Boris, additional

Published
2016
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