@inproceedings{rishu-etal-2024-uom,
    title = "{U}o{M}-{DFKI} submission to the low resource shared task",
    author = "Rishu, Kumar  and
      Williams, Aiden  and
      Borg, Claudia  and
      Ostermann, Simon",
    editor = "Salesky, Elizabeth  and
      Federico, Marcello  and
      Carpuat, Marine",
    booktitle = "Proceedings of the 21st International Conference on Spoken Language Translation (IWSLT 2024)",
    month = aug,
    year = "2024",
    address = "Bangkok, Thailand (in-person and online)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2024.iwslt-1.33/",
    doi = "10.18653/v1/2024.iwslt-1.33",
    pages = "280--285",
    abstract = "This system description paper presents the details of our primary and contrastive approaches to translating Maltese into English for IWSLT 24. The Maltese language shares a large vocabulary with Arabic and Italian languages, thus making it an ideal candidate to test the cross-lingual capabilities of recent state-of-the-art models. We experiment with two end-to-end approaches for our submissions: the Whisper and wav2vec 2.0 models. Our primary system gets a BLEU score of 35.1 on the combined data, whereas our contrastive approach gets 18.5. We also provide a manual analysis of our contrastive approach to identify some pitfalls that may have caused this difference."
}