A Machine Learning Approach to Measurement of Text Readability for EFL Learners Using Various Linguistic Features

نویسندگان

  • Katsunori Kotani
  • Takehiko Yoshimi
  • Hitoshi Isahara
چکیده

The present paper introduces and evaluates a readability measurement method designed for learners of EFL (English as a foreign language). The proposed readability measurement method (a regression model) estimates the text readability based on linguistic features, such as lexical, syntactic and discourse features. Text readability refers to the comprehension rate of a text (0.0-1.0). The experimental results showed that the proposed readability measurement method yielded higher accuracy than a baseline method, which provides the mode value of the distribution of the comprehension rate data as the estimated value for any input.

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تاریخ انتشار 2012