Manipuri is both a minority and morphologically rich language with genetic features similar to Tibeto Burman languages. It has Subject-Object-Verb (SOV) order, agglutinative verb morphology and is monosyllabic. Morphology and syntax are not clearly distinguished in this language. Natural Language Processing (NLP) is a useful research field of computer science that deals with processing of a large amount of natural language corpus. The NLP applications encompass E-Dictionary, Morphological Analyzer, Reduplicated Multi-Word Expression (RMWE), Named Entity Recognition (NER), Part of Speech (POS) Tagging, Machine Translation (MT), Word Net, Word Sense Disambiguation (WSD) etc. In this paper, we present a study on the advancements in NLP applications for Manipuri language, at the same time presenting a comparison table of the approaches and techniques adopted and the results obtained of each of the applications followed by a detail discussion of each work.

Statistical Machine Translation (SMT) is one ruling approach adopted for developing major translation systems today. Here, we report a phrase-based SMT system from English to Manipuri. The variance in the structure and morphology between English and Manipuri languages and the lack of resources for Manipuri languages pose a significant challenge in developing an MT system for the language pair. In comparison, English has poor morphology and SVO structure and belongs to the Indo-European family. Manipuri language has richer morphology and SOV structure and belongs to the Sino-Tibetan family. Manipuri has two scripts- Bengali script and Meitei script. Here the Bengali script is used for developing the system. Our system uses the Moses toolkit. We train and test the system using the tourism, agriculture and entertainment corpus. Further, we use the BLEU metric to evaluate the systems' performance.

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