Author: B'erard, Alexandre; Kim, Zae Myung; Nikoulina, Vassilina; Park, Eunjeong L.; Gall'e, Matthias
                    Title: A Multilingual Neural Machine Translation Model for Biomedical Data  Cord-id: kzdx95yc  Document date: 2020_8_6
                    ID: kzdx95yc
                    
                    Snippet: We release a multilingual neural machine translation model, which can be used to translate text in the biomedical domain. The model can translate from 5 languages (French, German, Italian, Korean and Spanish) into English. It is trained with large amounts of generic and biomedical data, using domain tags. Our benchmarks show that it performs near state-of-the-art both on news (generic domain) and biomedical test sets, and that it outperforms the existing publicly released models. We believe that
                    
                    
                    
                     
                    
                    
                    
                    
                        
                            
                                Document: We release a multilingual neural machine translation model, which can be used to translate text in the biomedical domain. The model can translate from 5 languages (French, German, Italian, Korean and Spanish) into English. It is trained with large amounts of generic and biomedical data, using domain tags. Our benchmarks show that it performs near state-of-the-art both on news (generic domain) and biomedical test sets, and that it outperforms the existing publicly released models. We believe that this release will help the large-scale multilingual analysis of the digital content of the COVID-19 crisis and of its effects on society, economy, and healthcare policies. We also release a test set of biomedical text for Korean-English. It consists of 758 sentences from official guidelines and recent papers, all about COVID-19.
 
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