Contextual Spelling Correction

摘要

Spelling correction is commonly a critical task for a variety of NLP tools. Some systems assist users by offering a set of possible corrections for a given misspelt word. An automatic spelling correction system would be able to choose only one or, at least, to rank them according to a certain criterion. We present a dynamic framework which allows us to combine spelling correction and Part-of-Speech tagging tasks in an efficient way. The result is a system capable of ranking the set of possible corrections taking the context of the erroneous words into account.