The European Association for Machine Translation (EAMT) invites everyone interested in machine translation, translation-related tools and resources to participate in this conference.
The EAMT invites entries for its 2017 EAMT Best Thesis Award for a PhD or equivalent thesis on a topic related to machine translation
The 16th Machine Translation Summit, organized by the Asia-Pacific Association for Machine Translation (AAMT), will be held at Nagoya University, Japan, in September 18-22 2017.
The 2017 EAMT conference will be held in Prague, Czech Republic, on May 28 – 31
Submission deadline for proposals: October 15, 2016, 23:59 CESTOlder news
DCU MT GROUP RELEASES FREE/OPEN-SOURCE EBMT SYSTEM 'OpenMaTrEx'
The Centre for Next Generation Localization’s (CNGL) Machine Translation group, led by Prof. Andy Way at Dublin City University (DCU), announces the release of ‘OpenMaTrEx’, a free/open-source example-based machine translation (EBMT) system based on the marker hypothesis. The OpenMaTrEx EBMT system release comprises a marker-driven chunker (based on Green’s “marker hypothesis”), a collection of chunk aligners, and two engines: one based on the simple proof-of-concept monotone recombinator (released last January as 'Marclator') and a Moses-based decoder. OpenMaTrEx is a free/open-source version of the basic components of MaTrEx, the data-driven machine translation system designed by the Machine Translation group at the School of Computing of Dublin City University.
This free/open-source release results from collaboration with Prof. Mikel L. Forcada of Universitat d’Alacant in Spain who is currently a visiting researcher within the CNGL MT group at DCU through an ETS Walton Award from Science Foundation Ireland (SFI). Through SFI funding of the Centre for Next Generation Localisation and additional funding from EU FP7 research projects currently coming on stream, DCU now boasts one of the largest academic research groups focused on MT worldwide. The OpenMaTrEx release is an important step in a strategy of participation in the free/open-source community in parallel with a programme of commercial engagement with companies interested in adopting, tuning and deploying machine translation technology.
Over the past number of years, Prof Andy Way has led the MT group at DCU in pursuing corpus-based approaches to MT, which have culminated in the MaTrEx system, a modular, maintainable and efficient data-driven machine translation system which combines example-based machine translation (EBMT) and statistical machine translation (SMT) and which consistently ranks as one of the top-performing MT systems in open machine translation evaluations (e.g. WMT-09, WMT-10 IWSLT-09, etc.).
DCU MT Group: http://nclt.dcu.ie/mt
Free/open-source MT systems: http://www.computing.dcu.ie/~mforcada/fosmt.html