Welcome to Moses!
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). Once you have a trained model, an efficient search algorithm quickly finds the highest probability translation among the exponential number of choices.
- 4 March 2014 Bug fix release for Moses, now version 2.1.1
- 3 February The 2014 Machine Translation Marathon will take place in Trento, Italy from 8-13th September.
- 21 January 2014 Moses v 2.1 has been released!
- 26 March 2013 The 2013 Machine Translation Marathon (MTM2013) will take place in Prague, Czech Republic from 9-14th September
- 5 March 2013 What do you want to see in Moses v2.0? See here for projects and how to suggest them.
- 28 January 2013 Moses v 1.0 has been released!
- 12 October 2012 Moses v 0.91 released
- February 2012: Moses development is being supported by the EU under the MosesCore project
- September 2011: Moses now has a cruise control page to see the status of the current builds
- September 2011: Moses is now hosted on github
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
- University of Edinburgh, Scotland
- Charles University, Prague, Czech Republic
- Fondazione Bruno Kessler, Trento, Italy
- RWTH Aachen, Germany
- University of Maryland, College Park, United States
- Massachusetts Institute of Technology, United States
- US funding agencies DARPA, NSF, and Department of Defence
Open Source License
Moses is licensed under the LGPL.