Optimize the translation of Indian languages for large target vocabulary in neural machine translation using multi-head attention mechanism.

A popular approach in machine translation is neural machine translation. It predicts and translates word sequences using artificial neural networks, generally modelling full sentences in a single integrated model. It enables the translation of languages from one natural language into another with or without the assistance of human beings. Even though deep neural architecture-based machine translation produces accurate results when translating western languages, we are unable to straight away apply these algorithms to translate languages in India, primarily because good corpora are not readily available and our languages are generally morphologically bountiful in nature. This paper aims at providing a general overview on language translation, which consists of Neural Machine Translation and Natural Language Generation involving the translation of Indian languages. [ABSTRACT FROM AUTHOR]