@inproceedings{ohuoba-etal-2024-quantifying,
    title = "Quantifying the Contribution of {MWE}s and Polysemy in Translation Errors for {E}nglish{--}{I}gbo {MT}",
    author = "Ohuoba, Adaeze  and
      Sharoff, Serge  and
      Walker, Callum",
    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-1.43/",
    pages = "537--547",
    abstract = "In spite of recent successes in improving Machine Translation (MT) quality overall, MT engines require a large amount of resources, which leads to markedly lower quality for lesser-resourced languages. This study explores the case of translation from English into Igbo, a very low resource language spoken by about 45 million speakers. With the aim of improving MT quality in this scenario, we investigate methods for guided detection of critical/harmful MT errors, more specifically those caused by non-compositional multi-word expressions and polysemy. We have designed diagnostic tests for these cases and applied them to collections of medical texts from CDC, Cochrane, NCDC, NHS and WHO."
}