@inproceedings{simonsen-einarsson-2024-human,
    title = "A Human Perspective on {GPT}-4 Translations: Analysing {F}aroese to {E}nglish News and Blog Text Translations",
    author = "Simonsen, Annika  and
      Einarsson, Hafsteinn",
    editor = "Scarton, Carolina  and
      Prescott, Charlotte  and
      Bayliss, Chris  and
      Oakley, Chris  and
      Wright, Joanna  and
      Wrigley, Stuart  and
      Song, Xingyi  and
      Gow-Smith, Edward  and
      Bawden, Rachel  and
      S{\'a}nchez-Cartagena, V{\'i}ctor M  and
      Cadwell, Patrick  and
      Lapshinova-Koltunski, Ekaterina  and
      Cabarr{\~a}o, Vera  and
      Chatzitheodorou, Konstantinos  and
      Nurminen, Mary  and
      Kanojia, Diptesh  and
      Moniz, Helena",
    booktitle = "Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 1)",
    month = jun,
    year = "2024",
    address = "Sheffield, UK",
    publisher = "European Association for Machine Translation (EAMT)",
    url = "https://preview.aclanthology.org/ingest-emnlp/2024.eamt-1.7/",
    pages = "24--36",
    abstract = "This study investigates the potential of Generative Pre-trained Transformer models, specifically GPT-4, to generate machine translation resources for the low-resource language, Faroese. Given the scarcity of high-quality, human-translated data for such languages, Large Language Models' capabilities to produce native-sounding text offer a practical solution. This approach is particularly valuable for generating paired translation examples where one is in natural, authentic Faroese as opposed to traditional approaches that went from English to Faroese, addressing a common limitation in such approaches. By creating such a synthetic parallel dataset and evaluating it through the Multidimensional Quality Metrics framework, this research assesses the translation quality offered by GPT-4. The findings reveal GPT-4{'}s strengths in general translation tasks, while also highlighting its limitations in capturing cultural nuances."
}