DESIGN AND IMPLEMENTATION OF DEVELOPING A LANGUAGE EXCHANGE APP, FOR PRACTICING CONVERSATION

Translation from one human language to another has been using the help of the capabilities of computer advances. There are a lot of machine translators nowadays, each adapts to different machine translator approaches. This thesis presents the distinction between two selected machine translator approaches, statistical machine translator (SMT) and hybrid machine translator (HMT). The research focuses on creating evaluation for two machine translator of different approaches by both textual studies and evaluation experiment. The result of this research is an evaluation of the translator system and also the translation result. This result is then hoped to add information into the history of machine translators. The communication between the users has improved a lot, credit goes to the social media platforms. As, they enhanced a lot in the past few years. Because of this, people around the world are communicating, addressing their issues and finding solutions for their queries. Nowadays, communication is very vital for the people. Here it comes with the importance of translating languages. Initially human translators were there to translate, but this is not the permanent solution for this problem. So, after many experiments and trials, the researchers bought the technology of machine translation, that has been widely used by experimenting with several languages and using different methods like Rule Based, Statistical Based and more recently, Neural Machine Translations. The machine translation entirely depends upon the datasets and how the machine got trained with the dataset. For most of the languages, there is a lack of adequate datasets, that have constituted into many challenges. Such kind of languages are stated as low resource languages.