A Statistical Model Based on the Three Head Words for Detecting Article Errors

  • Authors:

  • Ryo Nagata;Tatsuya Iguchi;Fumito Masui;Atsuo Kawai;Naoki Isu

  • Affiliations:

  • The author is with Hyogo University of Teacher Education, Hyogo-ken, 673--1494 Japan. E-mail: rnagata@info.hyogo-u.ac.jp,;The authors are with the Faculty of Engineering, Mie University, Tsu-shi, 514--8507 Japan.;The authors are with the Faculty of Engineering, Mie University, Tsu-shi, 514--8507 Japan.;The authors are with the Faculty of Engineering, Mie University, Tsu-shi, 514--8507 Japan.;The authors are with the Faculty of Engineering, Mie University, Tsu-shi, 514--8507 Japan.

  • Venue:
  • IEICE - Transactions on Information and Systems
  • Year:
  • 2005

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Abstract

In this paper, we propose a statistical model for detecting article errors, which Japanese learners of English often make in English writing. It is based on the three head words --- the verb head, the preposition, and the noun head. To overcome the data sparseness problem, we apply the backed-off estimate to it. Experiments show that its performance (F-measure=0.70) is better than that of other methods. Apart from the performance, it has two advantages: (i) Rules for detecting article errors are automatically generated as conditional probabilities once a corpus is given; (ii) Its recall and precision rates are adjustable.