MateCat pushes what is considered the new frontier of Computer Assisted Translation(CAT) technology, that is, how to effectively and ergonomically integrate Machine Translation(MT) within the human translation workflow.

While today MT is mainly trained with the objective of creating the most comprehensible output, in MateCat we target MT technology that will minimize the translator’s post-edit effort.

To this end, MateCat is developing an enhanced web-based CAT tool that will offer new MT capabilities, such as automatic adaption to the translated content, online learning from user corrections, and automatic quality estimation.

The project builds on state-of-the-art MT and CAT technologies created by the project members, such as Moses, the most popular open source statistical MT toolkit, and MyMemory, the world’s largest Translation Memory (TM) built collaboratively via MT and human contributions.

Our ultimate goal is to create new CAT technology that will significantly enhance the productivity and user experience of professional translators. Hence, progress of MateCat is being systematically assessed through field tests, involving professional translators, working on real translation projects, and evaluating the utility and usability of our solutions.

The MateCat project is run by Fondazione Bruno Kessler (Italy), Translated srl (Italy), University of Edinburgh (UK), and Université du Maine (France). The project is funded by the European Union's grant 287688, under FP7-ICT-2011-7.

All the results of the project will be released under the Lesser General Public License (LGPL) from the Free Software Foundation.