Syntax-based Statistical Machine Translation (Synthesis Lectures on Human Language Technologies) - Tapa blanda

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Philip Williams is a Research Associate at the University of Edinburgh, where he completed his Ph.D. in 2014. His main research interest is the integration of linguistic information into statistical machine translation. In his thesis, he applied unification-based constraints to syntax-based statistical machine translation. He is the main contributor to the syntax-based models in the Moses toolkit.Rico Sennrich is a Research Associate at the University of Edinburgh. He received his Ph.D. in Computational Linguistics from the University of Zurich in 2013. His research focuses on data-driven natural language processing, in particular machine translation, syntax, and morphology. His contributions to syntax-based machine translation include a more efficient algorithm for SCFG decoding, and novel models for syntactic language modelling and productive generation of compounds. He developed syntax-based SMT systems for English-German that were tied for first place in the shared translationtasks of WMT 2014 and 2015.Rico Sennrich is a Research Associate at the University of Edinburgh. He received his Ph.D. in Computational Linguistics from the University of Zurich in 2013. His research focuses on data-driven natural language processing, in particular machine translation, syntax, and morphology. His contributions to syntax-based machine translation include a more efficient algorithm for SCFG decoding, and novel models for syntactic language modelling and productive generation of compounds. He developed syntax-based SMT systems for English-German that were tied for first place in the shared translation tasks of WMT 2014 and 2015.Philipp Koehn is a Professor of Computer Science at Johns Hopkins University, where he is affiliated with the Center for Language and Speech Processing. He also is the Chair of Machine Translation at the University of Edinburgh. He received his Ph.D. in 2003 from the University of Southern California. He is the creator and maintainer of Moses, the de facto statistical machine translation system, used throughout the world in both research and industry. He is a co-founder of the WMT Conference on Statistical Machine Translation, and author of the 2009 textbook Statistical Machine Translation.