Moses is a statistical machine translation system that allows you to automatically train translation models for any language pair. All you need is a collection of translated texts (parallel corpus). An efficient search algorithm finds quickly the highest probability translation among the exponential number of choices.
The released software includes a command line executable which can used for decoding. The source code for the decoder, can be downloaded from github. Download the complete snapshot from github. This repository also contains regression tests, should you be interested in enhancing the decoder.
Learn about the decoder, training models, and tuning. Follow the step-by-step guide. The documentation available at this web side is also compiled in a printable manual.
The development of Moses is mainly supported under the MosesCore, EuroMatrixPlus, LetsMT, EuroMatrix, META-NET, and TC-STAR projects funded by the European Commission under Framework Programme 7 and 6, and received additional support from
Moses is licensed under the LGPL.