In order to accomplish the tasks of identifying incorrect characters and error correction, we developed two error detection systems with different dictionaries. First system, called CKIP-WS, adopted the CKIP word segmentation system which based on CKIP dictionary as its core detection procedure; another system, called G1-WS, used Google 1T uni-gram data to extract pairs of potential error word and correction candidates as dictionary. Both detection systems use the confusion character set provided by the bakeoff organizer to reduce the suggested correction candidates. A simple maximizing tri-gram frequency model based on Google 1T tri-gram was designed to validate and select the correct answers. The CKIP group of Academia Sinica participated in both Sub-Task1 (Error Detection) and Sub-Task2 (Error Correction) in 2013 SIGHAN bakeoff. The evaluation results show that the performances of our systems are pretty good on both tasks.
REF developed two segmentation systems with different dictionaries to search for errors.
Introduction to CKIP Chinese Spelling Check System for SIGHAN Bakeoff 2013 Evaluation
SIGHAN@IJCNLP
Computer Science