Abstract
Noisy channel models, widely used in modern spellers, cope with typical misspellings, but do not work well with infrequent and difficult spelling errors. In this paper, we have improved the noisy channel approach by iterative stochastic search for the best correction. The proposed algorithm allowed us to avoid local minima problem and improve the F1 measure by 6.6% on distant spelling errors. © 2014 Association for Computational Linguistics.
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CITATION STYLE
Gubanov, S., Galinskaya, I., & Baytin, A. (2014). Improved iterative correction for distant spelling errors. In 52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Proceedings of the Conference (Vol. 2, pp. 168–173). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/p14-2028
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