Mantra Rajbhasha Case Study

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Various NLP applications are found for languages of Indo-Aryan and Dravidian language families of India.
Part-of-Speech (POS) tagger classifies the POS of a given word. POS tagger and morph-analysers are developed at IIT Bombay for Hindi and Marathi.
Language barrier elimination is one of the goals of NLP domain. For this, machine translation systems are developed which convert the text from a source language to a target language. Following are the well-developed machine translation systems for Indian languages.
• ‘Mantra-Rajbhasha’ is a MAchiNe assisted TRAnslation tool is developed by C-DAC and is used by the government of India to translate documents. The translation system uses parser developed using Tree Adjoining Grammar (TAG). The English language text regarding Personnel administration, Finance, Agriculture, Information Technology, Education, HealthCare, Small-scale industries and Banking domains are inputted to this system. English, Hindi and Transfer Lexicon are used in this phase, which help to generate Hindi output. This further undergoes post-processing (optional phase) and finally gets translated to Hindi document. Another advantage of using Mantra is that it accepts input in more than one format. Many pre-processing and selection tools are also available to refine the output.
• One more domain specific translator is available that
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Bengali, Marathi, Hindi, Tamil and Telugu. It can process the query based on its language and retrieve results from the respective language. The summary is generated for each retrieved document and this feature helps the user in knowing the basic information about the overall content of the document without opening it. For Tamil language, UNL based semantic search facility is also provided in

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