machine learning - spell checker uses language model -

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i spell checker use language model.

i know there lot of spell checkers such hunspell, see doesn't relate context, token-based spell checker.

for example,

i lick eating banana

so here @ token-based level no misspellings @ all, words correct, there no meaning in sentence. "smart" spell checker recognize "lick" correctly written word, may author meant "like" , there meaning in sentence.

i have bunch of correctly written sentences in specific domain, want train "smart" spell checker recognize misspelling , learn language model, such recognize thought "lick" written correctly, author meant "like".

i don't see hunspell has such feature, can suggest other spell checker, so.

see "the design of proofreading software service" raphael mudge. describes both data sources (wikipedia, blogs etc) , algorithm (basically comparing probabilities) of approach. source of system, after deadline, available, it's not actively maintained anymore.


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