Machine translation is being carried out by the researchers from quite a long time. However, it is still a dream to materialize flawless Machine Translator and the small numbers of researchers has focussed at translating Marathi Text to English. Perfect Machine Translation Systems have not yet been fully built because the fact that languages differ syntactically as well as morphologically. Majority of the researchers have opted for Statistical Machine translation whereas in this paper we have addressed the challenges of Rule based Machine Translation. The paper describes the major divergences observed in language Marathi and English and many challenges encountered while attempting to build machine translation system form Marathi to English using rule based approach. As there are exceptions to the rules and limit to the feasibility of maintaining knowledgebase, the practical machine translation from Marathi to English is a complex task
The translation divergence is a challenging problem in the area of machine translation. Language divergence arises when lexically and syntactically similar sentences of the source language do not translate into sentences that are similar in lexical and syntactic structure in the target language. A detailed study of divergence issues in machine translation is required for their proper classification and detection. Though a number of Machine Translation developers have given attention to this problem, it is difficult to derive general strategies which can be used for any language pair. In this paper, we discuss the translation pattern between English to Marathi and Marathi to English of various constructions to identify the structural and syntactic divergences in English-Marathi language pair.
Deep Learning techniques have significant progress in the last few years. Different designs and methods of the model have experimented to enhance the performance in various domains of Natural Language Processing (NLP). Machine Translation is a domain of NLP. In this paper, we have reviewed different Encoding-Decoding methods for Neural Machine Translation(NMT). We also, compare these various methods and put forward a past, present and future of Neural Machine Translation.