Suggestion Generation for Erroneous Words in Tamil Documents Using N-gram Technique

Abstract

A spell checker is a tool that finds and corrects erroneous words and grammatical mistakes in a text document. Spelling error detection and correction techniques are widely used by text editing systems, search engines, text to speech and speech to text conversion systems, machine translation systems and optical character recognition systems. The spell checkers for European languages and some Indic languages are well developed. However, perhaps, owing to Tamil being a morphologically rich and agglutinative language this has been a challenging task. Erroneous words and grammatical mistakes can occur in sentences due to various reasons. Erroneous words can be classified into two categories, namely non-word errors and real-word errors. This work aims to correct non-word errors in Tamil documents by suggesting alternatives. The proposed approach uses letter-level and word-level n-gram, stemming and hash table techniques. Test results show that the suggestions generated by the system are with 95% accuracy.