Hindi And Marathi to English Machine Transliteration using SVM

Abstract

Language transliteration is one of the important areas in NLP. Transliteration is very useful for converting the named entities (NEs) written in one script to another script in NLP applications like Cross Lingual Information Retrieval (CLIR), Multilingual Voice Chat Applications and Real Time Machine Translation (MT). The most important requirement of Transliteration system is to preserve the phonetic properties of source language after the transliteration in target language. In this paper, we have proposed the named entity transliteration for Hindi to English and Marathi to English language pairs using Support Vector Machine (SVM). In the proposed approach, the source named entity is segmented into transliteration units; hence transliteration problem can be viewed as sequence labeling problem. The classification of phonetic units is done by using the polynomial kernel function of Support Vector Machine (SVM). Proposed approach uses phonetic of the source language and n-gram as two features for transliteration.