Tony O’Dowd


2021


Neural Translation for European Union (NTEU)
Mercedes García-Martínez | Laurent Bié | Aleix Cerdà | Amando Estela | Manuel Herranz | Rihards Krišlauks | Maite Melero | Tony O’Dowd | Sinead O’Gorman | Marcis Pinnis | Artūrs Stafanovič | Riccardo Superbo | Artūrs Vasiļevskis
Proceedings of Machine Translation Summit XVIII: Users and Providers Track

The Neural Translation for the European Union (NTEU) engine farm enables direct machine translation for all 24 official languages of the European Union without the necessity to use a high-resourced language as a pivot. This amounts to a total of 552 translation engines for all combinations of the 24 languages. We have collected parallel data for all the language combinations publickly shared in elrc-share.eu. The translation engines have been customized to domain,for the use of the European public administrations. The delivered engines will be published in the European Language Grid. In addition to the usual automatic metrics, all the engines have been evaluated by humans based on the direct assessment methodology. For this purpose, we built an open-source platform called MTET The evaluation shows that most of the engines reach high quality and get better scores compared to an external machine translation service in a blind evaluation setup.

2020

pdf
Neural Translation for the European Union (NTEU) Project
Laurent Bié | Aleix Cerdà-i-Cucó | Hans Degroote | Amando Estela | Mercedes García-Martínez | Manuel Herranz | Alejandro Kohan | Maite Melero | Tony O’Dowd | Sinéad O’Gorman | Mārcis Pinnis | Roberts Rozis | Riccardo Superbo | Artūrs Vasiļevskis
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation

The Neural Translation for the European Union (NTEU) project aims to build a neural engine farm with all European official language combinations for eTranslation, without the necessity to use a high-resourced language as a pivot. NTEU started in September 2019 and will run until August 2021.


Lexically Constrained Decoding for Sequence Generation
Tony O’Dowd
Proceedings of the 14th Conference of the Association for Machine Translation in the Americas (Volume 2: User Track)

2019

pdf
Large-scale Machine Translation Evaluation of the iADAATPA Project
Sheila Castilho | Natália Resende | Federico Gaspari | Andy Way | Tony O’Dowd | Marek Mazur | Manuel Herranz | Alex Helle | Gema Ramírez-Sánchez | Víctor Sánchez-Cartagena | Mārcis Pinnis | Valters Šics
Proceedings of Machine Translation Summit XVII: Translator, Project and User Tracks

2016

pdf
Improving KantanMT Training Efficiency with fast_align
Dimitar Shterionov | Jinhua Du | Marc Anthony Palminteri | Laura Casanellas | Tony O’Dowd | Andy Way
Conferences of the Association for Machine Translation in the Americas: MT Users' Track