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  • 标题:Rapid Development of Competitive Translation Engines for Access to Multilingual COVID-19 Information
  • 本地全文:下载
  • 作者:Andy Way ; Rejwanul Haque ; Guodong Xie
  • 期刊名称:Informatics
  • 电子版ISSN:2227-9709
  • 出版年度:2020
  • 卷号:7
  • 期号:2
  • 页码:19-39
  • DOI:10.3390/informatics7020019
  • 出版社:MDPI Publishing
  • 摘要:Every day, more people are becoming infected and dying from exposure to COVID-19. Some countries in Europe like Spain, France, the UK and Italy have suffered particularly badly from the virus. Others such as Germany appear to have coped extremely well. Both health professionals and the general public are keen to receive up-to-date information on the effects of the virus, as well as treatments that have proven to be effective. In cases where language is a barrier to access of pertinent information, machine translation (MT) may help people assimilate information published in different languages. Our MT systems trained on COVID-19 data are freely available for anyone to use to help translate information (such as promoting good practice for symptom identification, prevention, and treatment) published in German, French, Italian, Spanish into English, as well as the reverse direction.
  • 关键词:machine translation; COVID-19; crisis translation; neural MT; automatic evaluation; human evaluation; online MT; rapid response MT machine translation ; COVID-19 ; crisis translation ; neural MT ; automatic evaluation ; human evaluation ; online MT ; rapid response MT
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