Bilingual Words and Phrase Mappings for Marathi and Hindi SMT

TL;DR

This paper explores enhancing Marathi-Hindi statistical machine translation by augmenting training data with lexical resources like word forms and phrase mappings, leading to improved translation quality especially with limited parallel data.

Contribution

It introduces methods for incorporating lexical resources into SMT systems for Marathi and Hindi, demonstrating improved coverage and translation quality.

Findings

Incremental quality improvement with more lexical resources.

Enhanced coverage with limited parallel corpus.

Effective use of lexical resources in SMT.

Abstract

Lack of proper linguistic resources is the major challenges faced by the Machine Translation system developments when dealing with the resource poor languages. In this paper, we describe effective ways to utilize the lexical resources to improve the quality of statistical machine translation. Our research on the usage of lexical resources mainly focused on two ways, such as; augmenting the parallel corpus with more vocabulary and to provide various word forms. We have augmented the training corpus with various lexical resources such as lexical words, function words, kridanta pairs and verb phrases. We have described the case studies, evaluations and detailed error analysis for both Marathi to Hindi and Hindi to Marathi machine translation systems. From the evaluations we observed that, there is an incremental growth in the quality of machine translation as the usage of various lexical resources increases. Moreover, usage of various lexical resources helps to improve the coverage and quality of machine translation where limited parallel corpus is available.