3 citations · 5 across the 3 of their papers we have counts for
4 papers · 1 filter
Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach
Víctor M. Sánchez-Cartagena, Miquel Esplà-Gomis, Juan Antonio Pérez-Ortiz +1
In the context of neural machine translation, data augmentation (DA) techniques may be used for generating additional training samples when the available parallel data are scarce.…
Estimating post-editing effort: a study on human judgements, task-based and reference-based metrics of MT quality
Carolina Scarton, Mikel L. Forcada, Miquel Esplà-Gomis +1
Devising metrics to assess translation quality has always been at the core of machine translation (MT) research. Traditional automatic reference-based metrics, such as BLEU, have s…
UAlacant machine translation quality estimation at WMT 2018: a simple approach using phrase tables and feed-forward neural networks
Miquel Esplà-Gomis, Felipe Sánchez-Martínez, Mikel L. Forcada
We describe the Universitat d'Alacant submissions to the word- and sentence-level machine translation (MT) quality estimation (QE) shared task at WMT 2018. Our approach to word-lev…
Using external sources of bilingual information for on-the-fly word alignment
Miquel Esplà-Gomis, Felipe Sánchez-Martínez, Mikel L. Forcada
In this paper we present a new and simple language-independent method for word-alignment based on the use of external sources of bilingual information such as machine translation s…