A Mixed Trigrams Approach for Context Sensitive Spell Checking

Authors:
Davide Fossati;Barbara Eugenio
Affiliations:
Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA;Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA
Venue:
CICLing '07 Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing
Year:
2009

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Abstract

This paper addresses the problem of real-word spell checking, i.e., the detection and correction of typos that result in real words of the target language. This paper proposes a methodology based on a mixed trigrams language model. The model has been implemented, trained, and tested with data from the Penn Treebank. The approach has been evaluated in terms of hit rate, false positive rate, and coverage. The experiments show promising results with respect to the hit rates of both detection and correction, even though the false positive rate is still high.