Decoding in JoshuaOpen Source, Parsing-Based Machine Translation

We describe a scalable decoder for parsing-based machine translation. e decoder is written in Java and implements all the essential algorithms described in (Chiang, 2007) and (Li and Khudanpur, 2008b): chart-parsing, n-gram language model integration, beamand cube-pruning, and k-best extraction. Additionally, parallel and distributed computing techniques are exploited to make it scalable. We demonstrate experimentally that our decoder is more than 30 times faster than a baseline decoder written in Python.