In this article an attempt to introduce the first Persian context sensitive spell checker, which tries to detect and correct the :eat-word spelling error of Persian text is presented. The proposed method is a statistical approach which uses Bayesian framework as its probabilistic model and also uses mutual information metric as a semantic relatedness measure between different Persian words. Our experiments on sample test data, shows that accuracy of correction method is about 80% with respect to Fl-measure.
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