The TALP-UPC Machine Translation Systems for WMT19 News Translation Task: Pivoting Techniques for Low Resource MT
Noé Casas, José A. R. Fonollosa, Carlos Escolano, Christine Basta, Marta R. Costa‐jussà · 2019
In this article, we describe the TALP-UPC research group participation in the WMT19 news translation shared task for Kazakh-English.Given the low amount of parallel training data, we resort to using Russian as pivot language, training subword-based statistical translation systems for Russian-Kazakh and Russian-English that were then used to create two synthetic pseudo-parallel corpora for Kazakh-English and English-Kazakh respectively.Finally, a self-attention model based on the decoder part of the Transformer architecture was trained on the two pseudoparallel corpora.