Search Results for author: Manuel Herranz

Found 10 papers, 0 papers with code

Neural Translation for the European Union (NTEU) Project

no code implementations EAMT 2020 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

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.

Translation

A User Study of the Incremental Learning in NMT

no code implementations EAMT 2020 Miguel Domingo, Mercedes García-Martínez, Álvaro Peris, Alexandre Helle, Amando Estela, Laurent Bié, Francisco Casacuberta, Manuel Herranz

Adaptive neural machine translation systems, able to incrementally update the underlying models under an online learning regime, have been proven to be useful to improve the efficiency of this workflow.

Incremental Learning Machine Translation +2

Eco.pangeamt: Industrializing Neural MT

no code implementations LREC 2020 Mercedes Garc{\'\i}a-Mart{\'\i}nez, Manuel Herranz, Am Estela, o, {\'A}ngela Franco, Laurent Bi{\'e}

Eco is Pangeanic{'}s customer portal for generic or specialized translation services (machine translation and post-editing, generic API MT and custom API MT).

Machine Translation Translation

How Much Does Tokenization Affect Neural Machine Translation?

no code implementations20 Dec 2018 Miguel Domingo, Mercedes Garcıa-Martınez, Alexandre Helle, Francisco Casacuberta, Manuel Herranz

Separating punctuation and splitting tokens into words or subwords has proven to be helpful to reduce vocabulary and increase the number of examples of each word, improving the translation quality.

Machine Translation Translation +1

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