Ensemble of Translators with Automatic Selection of the Best Translation – the submission of FOKUS to the WMT 18 biomedical translation task –

Cristian Grozea


Abstract
This paper describes the system of Fraunhofer FOKUS for the WMT 2018 biomedical translation task. Our approach, described here, was to automatically select the most promising translation from a set of candidates produced with NMT (Transformer) models. We selected the highest fidelity translation of each sentence by using a dictionary, stemming and a set of heuristics. Our method is simple, can use any machine translators, and requires no further training in addition to that already employed to build the NMT models. The downside is that the score did not increase over the best in ensemble, but was quite close to it (difference about 0.5 BLEU).
Anthology ID:
W18-6445
Volume:
Proceedings of the Third Conference on Machine Translation: Shared Task Papers
Month:
October
Year:
2018
Address:
Belgium, Brussels
Venues:
EMNLP | WMT | WS
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
644–647
Language:
URL:
https://aclanthology.org/W18-6445
DOI:
10.18653/v1/W18-6445
Bibkey:
Cite (ACL):
Cristian Grozea. 2018. Ensemble of Translators with Automatic Selection of the Best Translation – the submission of FOKUS to the WMT 18 biomedical translation task –. In Proceedings of the Third Conference on Machine Translation: Shared Task Papers, pages 644–647, Belgium, Brussels. Association for Computational Linguistics.
Cite (Informal):
Ensemble of Translators with Automatic Selection of the Best Translation – the submission of FOKUS to the WMT 18 biomedical translation task – (Grozea, 2018)
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PDF:
https://aclanthology.org/W18-6445.pdf