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2022 EMNLP EMNLP 2022

The SPECTRANS System Description for the WMT22 Biomedical Task

Abstract

AbstractThis paper describes the SPECTRANS submission for the WMT 2022 biomedical shared task. We present the results of our experiments using the training corpora and the JoeyNMT (Kreutzer et al., 2019) and SYSTRAN Pure Neural Server/ Advanced Model Studio toolkits for the language directions English to French and French to English. We compare the pre- dictions of the different toolkits. We also use JoeyNMT to fine-tune the model with a selection of texts from WMT, Khresmoi and UFAL data sets. We report our results and assess the respective merits of the different translated texts.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Natural Language Processing

Authors

Nicolas Ballier, Jean-Baptiste Yunès, Guillaume Wisniewski, Lichao Zhu, Maria Zimina

Topics

Machine Learning > Application Areas > Domain Adaptation Natural Language Processing > Applications > Machine Translation Deep Learning > Learning Types > Fine-Tuning

Keywords

domain adaptation neural machine translation biomedical translation pre-trained transformer
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