Abstract
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. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Otero, J., Graña, J., & Vilares, M. (2007). Contextual spelling correction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4739 LNCS, pp. 290–296). Springer Verlag. https://doi.org/10.1007/978-3-540-75867-9_37
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