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The concept and feasibility of modern statistical machine translation: theory, practice and industry applications

The concept and feasibility of modern statistical machine translation: theory, practice and industry applications

This video was recorded at 6th Russian Summer School in Information Retrieval (RuSSIR), Yaroslavl 2012. Our world is currently in an era of globalization, which implies increasing interaction and the intertwining of different language communities. Machine translation technology is one of the core components of efficient multilingual information environment and should be seen as a strategic issue in the framework of the modern multilingual community. Nowadays, statistical machine translation (SMT) is one of the most popular paradigms of MT. The aim of the course is to teach students the background, theory and implementation behind SMT systems. The course covers aspects of SMT technology from formal description to implementation. It is divided into three parts: theoretical background of SMT; introduction to the main SMT software; and SMT industry perspectives, along with open-source and commercial products. At the end of the course, students will be aware of the taxonomy of various approaches to SMT; the main research problems in the field; the MT industrial applications and they will be able to test and train real SMT systems using the open-source Moses toolkit.

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