Usage of Neural Network Methods for Automated Text Translation in Natural Languages

In this project is considered one of the most pressing problems of our time - the development of a machine translation (MT) system of natural texts. The current state and development trends of machine translation models are analyzed. Areas for improvement were identified, a comparison of the most successful MP systems was made (such as Google Translate, Yandex.Translate, Facebook translator, etc.). The method for automated text translation in the natural languages was proposed and developed based on the technology of the vector representation of the words Word2Vec from Google. The developed method has been applied to solve the problem of automating the process of searching, analyzing and translating articles for the infotainment Internet portal pluggedin.ru. The proposed approach showed its prospects, and further directions for the development of this task were identified. The work consists of an introduction, three main chapters, including a description of the conceptual ideas, existing solutions and implementations, an explanation of the problem formulation and the it's stages separation, the proposal of its own method and its program implementation and a list of literature consisting of 51 items.