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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Natural language processing (NLP) is a field of computer science and linguistics which concerned to the interactions between computers and human (natural) languages. Morphology is the identification, analysis and description of the structure of morphemes and other units of meaning in a language like words, affixes, and parts of speech. In our previous paper a Two-sided morphology analyst of adjectives in Persian were designed. It divides adjective's components into their parts of speech or an adjective can be made. Persian words to English form were converted by us. To solve this problem, in this paper a new filter for converting the Persian words to Pinglish format is designed. Using the adjective as an input of morphological analyzer is so easy.