Spelling check identifies incorrect writing words in documents. For the reason of input methods, Chinese spelling check is much different from English and it is still a challenging work. For the past decade years, most of the methods in detecting errors in documents are lexicon-based or probability-based, and much progress are made. In this paper, we propose a new method in Chinese spelling check by using maximum entropy (ME). Experiment shows that by importing a large raw corpus, maximum entropy can build a well-trained model to detect spelling errors in Chinese documents.
REF detected each character spelling error in a sentence using a maximum entropy model trained on a large corpus.
A Maximum Entropy Approach to Chinese Spelling Check
SIGHAN@IJCNLP
Computer Science