Improving the quality of Machine Translation using rule based tense synthesizer for Hindi

Translation of English documents into Hindi language is becoming an integral part for facilitating communication. The major population of India where 366 million people uses Hindi as primary language, for them providing information in Hindi is an important task the translation of English documents may be manually or automatically. When translation done manually the chances are rare for errors, but when we use any translation machines or engine the outputs received from these machines for Hindi have lots of grammatical mistakes or errors. One of the major issues observed is of tense. Thus, we propose solution to build a rule based tense synthesizer that would recognise the subject, verb and auxiliary verb, analyse the tense, then modify the verb and auxiliary verb according to the subject and put the sentence in the correct tense. This system could be integrated with Machine Translation engines to boost up the quality of Hindi translation.