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    Improved Iterative Correction for Distant Spelling Errors

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    Noisy channel models, widely used in modern spellers, cope with typical mis-spellings, but do not work well with infre-quent and difficult spelling errors. In this paper, we have improved the noisy chan-nel approach by iterative stochastic search for the best correction. The proposed al-gorithm allowed us to avoid local minima problem and improve the F1 measure by 6.6 % on distant spelling errors.
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