A technical reading in statistical and neural machines translation (SMT & NMT)

Automatic translation of natural languages has been an active body of research in the last decades, especially when it comes to statistical translation which uses machine learning algorithms for translation tasks. Machine translation being a key application in the field of natural language processing, it leads to develop many approaches namely, statistical machine translation and recently neural machine translation. In this paper, we present a survey of the state of the art, where we describe the context of the current research studies by reviewing both the statistical machine translation and neural machine translation, and an overview of the main strengths and limitations of the two approaches.