A Seq to Seq Machine Translation from Urdu to Chinese

Abstract

Machine translation (MT) is a subtype of computational linguistics that uses to implement the translation between different natural languages (NL). Simply word to word exchanging on machine translation is not enough to give desire result. Neural machine translation is one of the standard methods of machine learning which make a huge improvement in recent time especially in local and some national languages. However these languages translation are not enough and need to focus on it. In this research we translate Urdu to Chinese language with the help of neural machine translation (NMT) in deep learning methods. First we build a monolingual corpus of Urdu and Chinese languages, after that we train our model using neural machine translation (NMT) and then compare the data-test result to accurate translation with the help of BLEU score method.