Word Vector/Conditional Random Field-based Chinese Spelling Error Detection for SIGHAN-2015 Evaluation
Yih‐Ru Wang, Yuan‐Fu Liao · 2015
In order to detect Chinese spelling errors, especially for essays written by foreign learners, a word vector/conditional random field (CRF)based detector is proposed in this paper.The main idea is to project each word in a test sentence into a high dimensional vector space in order to reveal and examine their relationships by using a CRF.The results are then utilized to constrain the time-consuming language model rescoring procedure.Official SIGHAN-2015 evaluation results show that our system did achieve reasonable performance with about 0.601/0.564ac-curacies and 0.457/0.375F1 scores in the detection/correction levels.