NURS – Neural Machine Translation for Under-Resourced Scenarios
The project focuses on neural machine translation (NMT) for under-resourced scenarios, i.e. languages or technical domains, using sequence-to-sequence models. To improve the translation quality within under-resourced scenarios, the work will involve data curation due to the code-mixing phenomena within the training data, terminology identification as well as linguistic injunction into the neural models.
This project is co-funded by the European Regional Development Fund (ERDF) under Urelands’s European Structural and Investment Fund Programmes 2014-2020.