Riccardo Superbo


2021

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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.

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MultiTraiNMT: Training Materials to Approach Neural Machine Translation from Scratch
Gema Ramírez-Sánchez | Juan Antonio Pérez-Ortiz | Felipe Sánchez-Martínez | Caroline Rossi | Dorothy Kenny | Riccardo Superbo | Pilar Sánchez-Gijón | Olga Torres-Hostench
Proceedings of the Translation and Interpreting Technology Online Conference

The MultiTraiNMT Erasmus+ project aims at developing an open innovative syllabus in neural machine translation (NMT) for language learners and translators as multilingual citizens. Machine translation is seen as a resource that can support citizens in their attempt to acquire and develop language skills if they are trained in an informed and critical way. Machine translation could thus help tackle the mismatch between the desired EU aim of having multilingual citizens who speak at least two foreign languages and the current situation in which citizens generally fall far short of this objective. The training materials consists of an open-access coursebook, an open-source NMT web application called MutNMT for training purposes, and corresponding activities.

2020

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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.