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The ADAPT System Description for the IWSLT 2018 Basque to English Translation Task

2018-11-14 · IWSLT (EMNLP) 2018 10 · Alberto Poncelas, Andy Way, Kepa Sarasola

In this paper we present the ADAPT system built for the Basque to English Low Resource MT Evaluation Campaign. Basque is a low-resourced, morphologically-rich language. This poses a challenge for Neural Machine Translation models which usually achieve better performance when trained with large sets of data. Accordingly, we used synthetic data to improve the translation quality produced by a model built using only authentic data. Our proposal uses back-translated data to: (a) create new sentences, so the system can be trained with more data; and (b) translate sentences that are close to the test set, so the model can be fine-tuned to the document to be translated.

📄 PDF Abstract BibTeX arXiv:1811.05909

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