Moses for Mere Mortals

Moses for Mere Mortals (MMM) is a free open source software composed of a set of scripts designed to allow the automation of processes for the installation and operation of the Moses Open Source Translation System, a statistical machine translation system.
MMM builds a translation chain prototype with Moses + IRSTLM + RandLM + MGIZA.
The first version of Moses for Mere Mortals was published in November 2009, and it has been updated and tested on Linux - Ubuntu distributions. MMM is available in the GitHub Project Hosting website.
Overview.
Its main aims are to:
Even though the main thrust is centred on Linux, two Windows add-ins help to make the bridge from MS Windows to Linux and then back from Linux.
General features.
Moses allows the training of corpora where every word is presented together with, for instance, its respective lemma and/or part of speech tag (“factored training”). The scripts do not cover this type of training.
MMM consists of seven scripts for Linux, thoroughly tested with Ubuntu (12.04 and 14.04, 64-bit):
MMM comes with a 200,000-segment demonstration corpus — which is too small to do justice to the qualitative results achievable with Moses, but capable of giving a realistic view of the relative duration of the steps involved and useful to test whether the installation was correctly done. In order to get good results, one generally needs a corpus with several million segments. Each orthogonal corpus consists of two strictly aligned UTF-8 files, one in the source language and the other in the target language. No grammar knowledge is required, though some language pairs give better results than others. In a general way, morphologically rich languages give worse results.
Add-ins.
MMM also contains (for Windows and Linux):
MMM also contains the file "Nonbreaking_prefix.pt", a list of abbreviations specific to the Portuguese language, based on English and German versions already available with the Moses package.
Software features.
Moses for Mere Mortals also has some original features: