Context-sensitive Word Error Detection and Correction for Automatic Scoring System of English Writing


KIPS Transactions on Software and Data Engineering, Vol. 4, No. 1, pp. 45-56, Jan. 2015
10.3745/KTSDE.2015.4.1.45,   PDF Download:

Abstract

In this paper, we present a method that can detect context-sensitive word errors and generate correction candidates. Spelling error detection is one of the most widespread research topics, however, the approach proposed in this paper is adjusted for an automated English scoring system. A common strategy in context-sensitive word error detection is using a pre-defined confusion set to generate correction candidates. We automatically generate a confusion set in order to consider the characteristics of sentences written by second-language learners. We define a word error that cannot be detected by a conventional grammar checker because of part-of-speech ambiguity, and propose how to detect the error and generate correction candidates for this kind of error. An experiment is performed on the English writings composed by junior-high school students whose mother tongue is Korean. The f1 value of the proposed method is 70.48%, which shows that our method is promising comparing to the current-state-of-the art.


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Cite this article
[IEEE Style]
Y. S. Choi and K. J. Lee, "Context-sensitive Word Error Detection and Correction for Automatic Scoring System of English Writing," KIPS Transactions on Software and Data Engineering, vol. 4, no. 1, pp. 45-56, 2015. DOI: 10.3745/KTSDE.2015.4.1.45.

[ACM Style]
Yong Seok Choi and Kong Joo Lee. 2015. Context-sensitive Word Error Detection and Correction for Automatic Scoring System of English Writing. KIPS Transactions on Software and Data Engineering, 4, 1, (2015), 45-56. DOI: 10.3745/KTSDE.2015.4.1.45.