Rule Based Transliteration Scheme for English to Punjabi

TL;DR

This paper presents a rule-based transliteration scheme for converting English to Punjabi, focusing on phonological preservation and syllabification, to improve machine translation quality.

Contribution

It introduces a novel rule-based approach with syllabification and probability calculations for English-Punjabi transliteration, integrating rule-based and statistical methods.

Findings

Effective syllabification rules developed

Probabilistic model improves transliteration accuracy

Enhanced quality in machine translation applications

Abstract

Machine Transliteration has come out to be an emerging and a very important research area in the field of machine translation. Transliteration basically aims to preserve the phonological structure of words. Proper transliteration of name entities plays a very significant role in improving the quality of machine translation. In this paper we are doing machine transliteration for English-Punjabi language pair using rule based approach. We have constructed some rules for syllabification. Syllabification is the process to extract or separate the syllable from the words. In this we are calculating the probabilities for name entities (Proper names and location). For those words which do not come under the category of name entities, separate probabilities are being calculated by using relative frequency through a statistical machine translation toolkit known as MOSES. Using these probabilities we are transliterating our input text from English to Punjabi.