Demonstration of Joshua
Zhifei Li, Chris Callison-Burch, Chris Dyer, Juri Ganitkevitch, Sanjeev P. Khudanpur, Lane Schwartz, Wren N. G. Thornton, Jonathan R. Weese, Omar F. Zaidan · 2009
We describe Joshua (Li et al., 2009a), an open source toolkit for statistical machine translation. Joshua implements all of the algorithms required for translation via 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 distributed computing techniques for scalability. We also provide a demonstration outline for illustrating the toolkit's features to potential users, whether they be newcomers to the field or power users interested in extending the toolkit.