A Review of the Various Approaches for Text to Text Machine Translations

Machine translation (MT) is defined as a subfield of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to another. It is a key application in the field of natural language processing. At its basic level, MT performs simple substitution of words in one natural language for words in another. Effort to access documents from one language to another leads to the development of machine translation system which involves lots of heterogeneous features and its implementations. Approaches to machine translations are different and each of this approach has its own benefits and drawbacks. This study looks at the various approaches to machine translations and future needs in order to provide more robust and sensible system in the area of natural language processing which will be resistant and impervious to failure regardless of users' inputs. It is hopeful that researchers in the area of language processing can make use of our valuable improvement and suggestions.