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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 been 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. DOI: http://dx.doi.org/10.4038/icter.v3i1.2844ICTer Vol.3 No.1 2010

Grapheme-to-phoneme (G2P) conversion plays an important role in speech processing applications and other fields of computational linguistics. Sinhala must have a grapheme-to-phoneme conversion for speech processing because Sinhala writing system does not always reflect its actual pronunciations. This paper describes a rule basedG2P conversion method to convert Sinhala text strings into phonemic representations. We use a previously defined rule set and enhance it to get a more accurate G2P conversion. The performance of our rule-based system shows that the rulebased sound patterns are effective on Sinhala G2P conversion.