Abstract
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 0.601/0.564 ac-curacies and 0.457/0.375 F1 scores in the detection/correction levels.
Cite
CITATION STYLE
Wang, Y. R., & Liao, Y. F. (2015). Word vector/conditional random field-based chinese spelling error detection for SIGHAN-2015 evaluation. In Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015 (pp. 46–49). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w15-3108
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