Automated Error Detection and Correction of Chinese Characters in Written Essays Based on Weighted Finite-State Transducer

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Shudong Hao, Zongtian Gao, Mingqing Zhang, Yanyan Xu, Hengli Peng, Kaile Su, Dengfeng Ke

Published: 2013, Last Modified: 24 May 2026ICDAR 2013EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Chinese text error detection and correction is widely applicable, but the methods so far are not robust enough for industrial use. In this paper, a new method is proposed based on Tri-gram modeled-Weighted Finite-State Transducer (WFST). By integrating confusing-character table, beam search and A* search, we evaluate the performance on real test essays. Various experiments have been conducted to prove that the proposed method is effective with the recall rate of 85.68%, the detection accuracy of 91.22% and the correction accuracy of 87.30%.