@inproceedings{tarres-etal-2022-tackling,
title = "Tackling Low-Resourced Sign Language Translation: {UPC} at {WMT}-{SLT} 22",
author = "Tarres, Laia and
G{\'a}llego, Gerard I. and
Giro-i-nieto, Xavier and
Torres, Jordi",
booktitle = "Proceedings of the Seventh Conference on Machine Translation (WMT)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.wmt-1.97",
pages = "994--1000",
abstract = "This paper describes the system developed at the Universitat Polit{\`e}cnica de Catalunya for the Workshop on Machine Translation 2022 Sign Language Translation Task, in particular, for the sign-to-text direction. We use a Transformer model implemented with the Fairseq modeling toolkit. We have experimented with the vocabulary size, data augmentation techniques and pretraining the model with the PHOENIX-14T dataset. Our system obtains 0.50 BLEU score for the test set, improving the organizers{'} baseline by 0.38 BLEU. We remark the poor results for both the baseline and our system, and thus, the unreliability of our findings.",
}
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%0 Conference Proceedings
%T Tackling Low-Resourced Sign Language Translation: UPC at WMT-SLT 22
%A Tarres, Laia
%A Gállego, Gerard I.
%A Giro-i-nieto, Xavier
%A Torres, Jordi
%S Proceedings of the Seventh Conference on Machine Translation (WMT)
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates (Hybrid)
%F tarres-etal-2022-tackling
%X This paper describes the system developed at the Universitat Politècnica de Catalunya for the Workshop on Machine Translation 2022 Sign Language Translation Task, in particular, for the sign-to-text direction. We use a Transformer model implemented with the Fairseq modeling toolkit. We have experimented with the vocabulary size, data augmentation techniques and pretraining the model with the PHOENIX-14T dataset. Our system obtains 0.50 BLEU score for the test set, improving the organizers’ baseline by 0.38 BLEU. We remark the poor results for both the baseline and our system, and thus, the unreliability of our findings.
%U https://aclanthology.org/2022.wmt-1.97
%P 994-1000
Markdown (Informal)
[Tackling Low-Resourced Sign Language Translation: UPC at WMT-SLT 22](https://aclanthology.org/2022.wmt-1.97) (Tarres et al., WMT 2022)
ACL