Bilingual Machine Translation Using RNN Based Deep Learning
Janhavi R. Chaudhary, Ankit C. Patel · Zenodo (CERN European Organization for Nuclear Research) · 2018
Machine Translation using Deep Learning (Neural Machine Translation) is a newly proposed approach to machine translation. The term Machine Translation is used in the sense of translation of one language to another, with no human improvement. It can also be referred to as automated translation. Unlike the traditional statistical machine translation, the neural machine translation aims at building a single neural network that can be jointly tuned to maximize the translation performance. The models proposed recently for neural machine translation often belong to a family of encoder–decoders and encode a source sentence into a ?xed-length vector from which a decoder generates a translation. In this approach Neural Machine Translation technique will be used to translate Japanese language into English language. Tanaka corpus will be used in this approach. Japanese will be translated into English using improved Recurrent Neural Network(RNN).