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 latest release or the current snapshot from github.
Learn about the decoder, training models, and tuning. Follow the step-by-step guide to build a baseline translation system. The documentation available at this web side is also compiled in a printable manual.
The development of Moses is mainly supported by the European Union under the following projects:
It has received additional support from
Moses is licensed under the LGPL.