Improving the quality of Gujarati-Hindi Machine Translation through part-of-speech tagging and stemmer-assisted transliteration

TL;DR

This paper enhances Gujarati-Hindi machine translation by integrating part-of-speech tagging and stemming to improve transliteration accuracy, thereby increasing overall translation quality.

Contribution

It introduces a novel approach combining POS tagging and stemming to optimize transliteration in Indian language machine translation systems.

Findings

Improved transliteration accuracy demonstrated

Enhanced translation quality observed

Content preservation in transliteration process

Abstract

Machine Translation for Indian languages is an emerging research area. Transliteration is one such module that we design while designing a translation system. Transliteration means mapping of source language text into the target language. Simple mapping decreases the efficiency of overall translation system. We propose the use of stemming and part-of-speech tagging for transliteration. The effectiveness of translation can be improved if we use part-of-speech tagging and stemming assisted transliteration.We have shown that much of the content in Gujarati gets transliterated while being processed for translation to Hindi language.