@inproceedings{casas-etal-2019-talp,
title = "The {TALP}-{UPC} Machine Translation Systems for {WMT}19 News Translation Task: Pivoting Techniques for Low Resource {MT}",
author = "Casas, Noe and
Fonollosa, Jos{\'e} A. R. and
Escolano, Carlos and
Basta, Christine and
Costa-juss{\`a}, Marta R.",
booktitle = "Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-5311",
doi = "10.18653/v1/W19-5311",
pages = "155--162",
abstract = "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 pseudo-parallel corpora.",
}
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%0 Conference Proceedings
%T The TALP-UPC Machine Translation Systems for WMT19 News Translation Task: Pivoting Techniques for Low Resource MT
%A Casas, Noe
%A Fonollosa, José A. R.
%A Escolano, Carlos
%A Basta, Christine
%A Costa-jussà, Marta R.
%S Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
%D 2019
%8 aug
%I Association for Computational Linguistics
%C Florence, Italy
%F casas-etal-2019-talp
%X 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 pseudo-parallel corpora.
%R 10.18653/v1/W19-5311
%U https://aclanthology.org/W19-5311
%U https://doi.org/10.18653/v1/W19-5311
%P 155-162
Markdown (Informal)
[The TALP-UPC Machine Translation Systems for WMT19 News Translation Task: Pivoting Techniques for Low Resource MT](https://aclanthology.org/W19-5311) (Casas et al., 2019)
ACL