In this paper we describe the construction of a spell checker for Sinhala, the language spoken by the majority in Sri Lanka. Due to its morphological richness, the language is difficult to enumerate completely in a lexicon. The approach described is based on n-gram statistics and is relatively inexpensive to construct without deep linguistic knowledge. This approach is particularly useful as there are very few linguistic resources available for Sinhala at present. The proposed algorithm has

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... shown to be able to detect and correct many of the common spelling errors of the language. Results show a promising performance achieving an average accuracy of 82%. This technique can also be applied to construct spell checkers for other phonetic languages whose linguistic resources are scarce or non-existent.