Improve the detection of improperly used Chinese characters in students' essays with error model

Yong Zhi Chen, Shih Hung Wu, Ping Che Yang, Tsun Ku, Gwo Dong Chen

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

In this research, we propose a Chinese essay error detection system that can be used in online writing tutorial environment. The system consists of word segmentation, template module, and language model module. We build the system with a dictionary for word segmentation and generation of detection templates from news corpus. We also gather the character error probabilities from students' essays to build error model. Error types include pronunciation-related errors and composition-related errors. Our system provides two operating modes for users with different goals. For example, we can help students learn to write effectively by providing high precision correction mode; for teachers, we provide high correction detection mode which can help teachers to check students' essays.

Original languageEnglish
Pages (from-to)103-116
Number of pages14
JournalInternational Journal of Continuing Engineering Education and Life-Long Learning
Volume21
Issue number1
DOIs
StatePublished - Apr 2011

Keywords

  • Chinese essay error detection
  • Language model
  • Template matching

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