COIS810
Machine Translation

Course Description

This course introduces the fundamental concepts and advanced topics concerning the design and building of machine translation (MT) systems, with a focus on statistical approaches. It covers from the analysis of the source language in different levels to the generation of text in another language, emphasizing the corpus-based methods. The main contents include the overviews of translation architectures, translation paradigms, statistical translation models and algorithms, word-based translation, phrase-based translation, syntax-based translation, and evaluation metrics. Through hands-on experience with building translation systems, students will learn how to formulate and investigate research questions in machine translation.


Prerequisite

Programming algorithms and formal structures, Basic knowledge in artificial intelligence and Basic familiarity with logic, probability and statistics.


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