Probabilistic Detection of Context-Sensitive Spelling Errors
Royal Institute of Technology, Stockholm, Sweden
This article focuses on the evaluation of a novel algorithm for the detection of context-sensitive spelling errors. We present a fully automatic evaluation procedure with no requirements of manual work or resources annotated with spelling errors. The evaluation method is applicable to any language and tag set, and is easily adaptable to other NLP systems such as taggers and parsers.
Automatic evaluation, context-sensitive spelling errors