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\title{\bf \vspace{-2cm} {\huge M}OSES\\ 
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{\Large Statistical\\
Machine Translation\\
System\\[4mm]
User Manual and Code Guide}}
\author{Philipp Koehn\\
{\tt pkoehn@inf.ed.ac.uk}\\
University of Edinburgh\\[10mm] {\bf \small Abstract} \\
\parbox[t]{163mm}{\small $\;\;\;\;\;$ This document serves as user manual and code guide for the Moses machine translation decoder. The decoder was mainly developed by Hieu Hoang and Philipp Koehn at the University of Edinburgh and extended during a Johns Hopkins University Summer Workshop and further developed under EuroMatrix and GALE project funding. The decoder (which is part of a complete statistical machine translation toolkit) is the de facto benchmark for research in the field.\\
$\;\;\;\;\;$ This document serves two purposes: a user manual for the functions of the Moses decoder and a code guide for developers. In large parts, this manual is identical to documentation available at the official Moses decoder web site {\sf http://www.statmt.org/}. This document does not describe in depth the underlying methods, which are described in the text book {\em Statistical Machine Translation} (Philipp Koehn, Cambridge University Press, 2009).}
}

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\section*{Acknowledgments}
The Moses decoder was supported by the European Framework 6 projects EuroMatrix,
TC-Star, the European Framework 7 projects EuroMatrixPlus, Let's MT, META-NET and MosesCore
 and the DARPA GALE project, as well as several universities such as the University of Edinburgh, the University of Maryland, ITC-irst, Massachusetts Institute of Technology, and others.

Contributors are too many to mention, but it is important to stress the substantial contributions from Hieu Hoang, Chris Dyer, Josh Schroeder, Marcello Federico, Richard Zens, and Wade Shen. Moses is an open source project under the guidance of Philipp Koehn.


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