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Machine Translation is a well-known sub field of Computational Linguistics that investigates the use of software to automatically translate text or speech from one language to another. It becomes a challenge to handle language specific features when it comes to machine translation such as differences in linguistic grammar, translation of idioms, and the isolation of anomalies particular to a language. Statistical and neural methods are being used extensively today to solve this problem and to get better translations. In this course we would focus on building a fast and high performance statistical machine translation system learning the various methodologies, tools and techniques widely used to accomplish it. In this course you will get hands-on in building your own statistical machine translation system using the Open Source Moses framework.
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