A Spelling Correction Method for Traditional Mongolian Based on Statistical Translation Framework
SU Chuanji · Zhongwen xinxi xuebao · 2013
In traditional Mongolian electronic textsencoded inUnicode,spelling errors are very common.The cost of correcting spelling errors artificially is extremely high.This paper proposed an automatic spellingcorrection method for traditional Mongolian based on statistical machine translation framework,and we regardspelling correction task as a translation work which translates the wrong words to the correct words.This paper used the improved phrasebased statistical machine translation model to build spelling correction model.We use this model tocorrect the rawtext.We used atest set whichcontained 1 026correct words and 1 102wrong words to test our method,Experimental results show that our method can correct spelling errors quickly and efficiently without special language knowledge.The percentage of correct words in ourproofreadtextcan reach to 97.55%.