Comparison of SMT and RBMT; The Requirement of Hybridization for Marathi-Hindi MT
This work addresses machine translation challenges for the Marathi-Hindi language pair, but it is incremental as it applies existing methods to a new language combination.
The authors compared Statistical Machine Translation (SMT) and Rule-Based Machine Translation (RBMT) for Marathi-Hindi translation, finding that SMT offers advantages like easier development and maintenance, even with a small training corpus, for high-quality domain-specific tasks.
We present in this paper our work on comparison between Statistical Machine Translation (SMT) and Rule-based machine translation for translation from Marathi to Hindi. Rule Based systems although robust take lots of time to build. On the other hand statistical machine translation systems are easier to create, maintain and improve upon. We describe the development of a basic Marathi-Hindi SMT system and evaluate its performance. Through a detailed error analysis, we, point out the relative strengths and weaknesses of both systems. Effectively, we shall see that even with a small amount of training corpus a statistical machine translation system has many advantages for high quality domain specific machine translation over that of a rule-based counterpart.