Title :
Automated Error Detection and Correction of Chinese Characters in Written Essays Based on Weighted Finite-State Transducer
Author :
Shudong Hao ; Zongtian Gao ; Mingqing Zhang ; Yanyan Xu ; Hengli Peng ; Kaile Su ; Dengfeng Ke
Author_Institution :
Sch. of Inf. Sci. & Technol., Beijing Forestry Univ., Beijing, China
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%.
Keywords :
character recognition; natural language processing; search problems; text detection; transducers; A* search; Chinese characters; automated error detection and correction; beam search; confusing-character table; real test essays; tri-gram modeled-weighted finite-state transducer; written essays; Accuracy; Containers; Context; Decoding; Educational institutions; Error correction; Transducers; Error correction; Error detection; N-gram language model; Weighted Finite-State Transducer (WFST);
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
Conference_Location :
Washington, DC
DOI :
10.1109/ICDAR.2013.156