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Cracking the Language Barrier: Coordination, Evaluation and Resources for European MT Research

Cracking the Language Barrier: Coordination, Evaluation and Resources for European MT Research

  • Duration:

The European machine translation (MT) research community is experiencing increased pressure for rapid success – from the legal and political frameworks and schedules of the EU, such as the Digital Single Market, but also from the globalising business world. At the same time, the research community has to cope with a striking disproportion between the scope of the challenges and the available resources, especially for translation to and from languages that have only fragmentary or no technological support at all.

CRACKER pushes towards an improvement of MT research in terms of efficiency and effectiveness by implementing the successful example of other disciplines where massively collaborative research on shared resources – guided by interoperability, standardisation, agreed major challenges and comprehensive success metrics – has led to breakthroughs that would have been impossible otherwise. The nucleus of this new research, development, and innovation strategy towards high-quality MT is the group of projects funded through Horizon 2020 Call ICT-17a/b (partly extending to relevant FP7 actions such as QTLeap, LIDER and MLi), that will be supported by CRACKER (ICT-17c) in coordination, evaluation and resources.

In order to achieve its challenging goals efficiently, CRACKER will build upon, consolidate and extend initiatives for collaborative MT research supported by earlier EU-funded actions. These include evaluation campaigns such as the Workshop on Statistical Machine Translation (WMT) and the International Workshop on Spoken Language Translation (IWSLT), the META-SHARE open infrastructure for sharing language resources and technologies with extensions for MT assembled by QTLaunchPad, and open-source tool building and training (MT Marathons). Coordination, communication and outreach to user communities will build upon existing networks and communication infrastructures such as the META-FORUM event series and strong involvement of industrial associations.

Funding Notice: The project CRACKER has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 645357.


  • Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Germany
  • Charles University in Prague, Czech Republic
  • Evaluations and Language Resources Distribution Agency, France
  • Fondazione Bruno Kessler, Italy
  • Athena Research and Innovation Center in Information, Communication and Knowledge Technologies, Greece
  • University of Edinburgh, United Kingdom
  • University of Sheffield, United Kingdom


EU - European Union

EU - European Union

Publications about the project

Georg Rehm; Stefanie Hegele

In: Nicoletta Calzolari; Khalid Choukri; Christopher Cieri; Thierry Declerck; Sara Goggi; Koiti Hasida; Hitoshi Isahara; Bente Maegaard; Joseph Mariani; Hélène Mazo; Asuncion Moreno; Jan Odijk; Stelios Piperidis; Takenobu Tokunaga (Hrsg.). Proceedings of the 11th Language Resources and Evaluation Conference (LREC 2018). International Conference on Language Resources and Evaluation (LREC-2018), Miyazaki, Japan, Pages 3282-3289, European Language Resources Association (ELRA), 5/2018.

To the publication

Daniel Zeman; Martin Popel; Milan Straka; Jan Hajic; Joakim Nivre; Filip Ginter; Juhani Luotolahti; Sampo Pyysalo; Slav Petrov; Martin Potthast; Francis Tyers; Elena Badmaeva; Memduh Gokirmak; Anna Nedoluzhko; Silvie Cinkova; Jan Hajic jr.; Jaroslava Hlavacova; Václava Kettnerová; Zdenka Uresova; Jenna Kanerva; Stina Ojala; Anna Missilä; Christopher D. Manning; Sebastian Schuster; Dima Taji Siva Reddy; Nizar Habash; Herman Leung; Marie-Catherine de Marneffe; Manuela Sanguinetti; Maria Simi; Hiroshi Kanayama; Valeria dePaiva; Kira Droganova; Héctor Martínez Alonso; Çağrı Çöltekin; Umut Sulubacak; Hans Uszkoreit; Vivien Macketanz; Aljoscha Burchardt; Kim Harris; Katrin Marheinecke; Georg Rehm; Tolga Kayadelen; Mohammed Attia; Ali Elkahky; Zhuoran Yu; Emily Pitler; Saran Lertpradit; Michael Mandl; Jesse Kirchner; Hector Fernandez Alcalde; Jana Strnadová; Esha Banerjee; Ruli Manurung; Antonio Stella; Atsuko Shimada; Sookyoung Kwak; Gustavo Mendonca; Tatiana Lando; Rattima Nitisaroj; Josie Li

In: Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies. Conference on Computational Natural Language Learning (CoNLL-2017), The SIGNLL Conference on Computational Natural Language Learning, August 3-4, Vancouver, BC, Canada, Pages 1-19, Association for Computational Linguistics, 2017.

To the publication