This introductory text to statistical machine translation (SMT) provides all of the theories and methods needed to build a statistical machine translator, such as Google Language Tools and Babelfish. In general, statistical techniques allow automatic translation systems to be built quickly for any language-pair using only translated texts and generic software. With increasing globalization, statistical machine translation will be central to communication and commerce. Based on courses and tutorials, and classroom-tested globally, it is ideal for instruction or self-study, for advanced undergraduates and graduate students in computer science and/or computational linguistics, and researchers in natural language processing. The companion website provides open-source corpora and tool-kits.
This class-tested text establishes background in NLP and statistics, then develops the basics through to current research. By the end readers can build their own translation systems. For advanced undergraduates in computer science, graduate students in computer science and computational linguistics, and researchers in NLP; for instruction or self-study.
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