Abstract

Language transliteration is one of the important area in natural language processing. Accurate transliteration of named entities plays an important role in the performance of machine translation and cross-language information retrieval processes. The transliteration model must be design in such a way that the phonetic structure of words should be preserve as closely as possible. We have developed hybrid (statistical +rules) approach based transliteration system of person names; from a person name written in Punjabi (Gurumukhi Script), the system produces its English (Roman Script) transliteration. Experiments have shown that the performance is sufficiently high. The overall accuracy of system comes out to be 95.23%.

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