Machine Translation in Indian Languages: Challenges and Resolution

TL;DR

This paper addresses structural and morphological challenges in English to Indian language machine translation by employing pre-ordering and suffix separation techniques, leading to improved translation quality.

Contribution

It introduces a novel combination of pre-ordering and suffix separation methods to enhance statistical machine translation for Indian languages.

Findings

Pre-ordering improves syntactic alignment.

Suffix separation reduces morphological divergence.

Translation quality is significantly improved.

Abstract

English to Indian language machine translation poses the challenge of structural and morphological divergence. This paper describes English to Indian language statistical machine translation using pre-ordering and suffix separation. The pre-ordering uses rules to transfer the structure of the source sentences prior to training and translation. This syntactic restructuring helps statistical machine translation to tackle the structural divergence and hence better translation quality. The suffix separation is used to tackle the morphological divergence between English and highly agglutinative Indian languages. We demonstrate that the use of pre-ordering and suffix separation helps in improving the quality of English to Indian Language machine translation.