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Summary: Joshua: An Open Source Toolkit for Parsing-based Machine Translation
Zhifei Li, Chris Callison-Burch, Chris Dyer,
Juri Ganitkevitch,+
Sanjeev Khudanpur,
Lane Schwartz, Wren N. G. Thornton, Jonathan Weese and Omar F. Zaidan
Center for Language and Speech Processing, Johns Hopkins University, Baltimore, MD
Computational Linguistics and Information Processing Lab, University of Maryland, College Park, MD
+ Human Language Technology and Pattern Recognition Group, RWTH Aachen University, Germany
Natural Language Processing Lab, University of Minnesota, Minneapolis, MN
Abstract
We describe Joshua, an open source
toolkit for statistical machine transla-
tion. Joshua implements all of the algo-
rithms required for synchronous context
free grammars (SCFGs): chart-parsing, n-
gram language model integration, beam-
and cube-pruning, and k-best extraction.
The toolkit also implements suffix-array
grammar extraction and minimum error
rate training. It uses parallel and dis-
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