Phrase-based Memory-based Machine Translation
Python Shell C++


PBMBMT: Phrase-based Memory-based Machine Translator
    by Maarten van Gompel
    Supervised by Antal van den Bosch
    Induction of Linguistic Knowledge Research Group (ILK)
    Tilburg Centre of Cognition and Communication (TiCC)
    Tilburg University
PBMBMT Homepage:

We present PBMBMT, a system for phrase-based memory-based machine translation. This is a type of example-based machine translation in which the translation model takes the form of approximate $k$-nearest neighbour classifiers trained to map words or phrases in context to a target word or phrase. PBMBMT embraces the concept of phrases, as opposed to the single words or fixed $n$-grams that earlier work in memory-based machine translation focused on. PBMBMT usually employs a phrase translation table, such as generated by Moses, as the basis for the generation of training and test instances for the classifiers.

The system is available under the GNU Public License v3 and is suited primarily for research purposes. 

For installation instructions see INSTALL or the website, for usage instructions, we refer only to the webpage at , which contains a how-to.

The theory is extensively described in the following publications, reading the first is strongly recommended before attempting to use the system!

[1] M. Van Gompel, A. Van den Bosch, and P. Berck. Advances in Memory-based Machine Translation (awaiting approval for publication in special-issue MT Journal)

[2] M. Van Gompel, A. Van den Bosch, and P. Berck. Extending memory-based machine
translation to phrases. In M. Forcada and A. Way, editors, Proceedings of the Third
Workshop on Example-Based Machine Translation, pages 79–86, Dublin, Ireland, 2009

[3] M. van Gompel. Phrase-based Memory-based Machine Translation. Master's thesis. Tilburg. 2009

[4] A. Van den Bosch and P. Berck. Memory-based machine translation and language modeling. 
The Prague Bulletin of Mathematical Linguistics, 91:17–26, 2009.