@inproceedings{chellaf-etal-2025-lia,
    title = "{LIA} and {ELYADATA} systems for the {IWSLT} 2025 low-resource speech translation shared task",
    author = "Chellaf, Chaimae  and
      Elleuch, Haroun  and
      Istaiteh, Othman  and
      Fortun{\'e} KPONOU, D.  and
      Bougares, Fethi  and
      Est{\`e}ve, Yannick  and
      Mdhaffar, Salima",
    editor = "Salesky, Elizabeth  and
      Federico, Marcello  and
      Anastasopoulos, Antonis",
    booktitle = "Proceedings of the 22nd International Conference on Spoken Language Translation (IWSLT 2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria (in-person and online)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/acl25-workshop-ingestion/2025.iwslt-1.27/",
    pages = "274--281",
    ISBN = "979-8-89176-272-5",
    abstract = "In this paper, we present the approach and system setup of our participation in the IWSLT 2025 low-resource speech translation shared task. We submitted systems for three language pairs, namely Tunisian Arabic to English, North Levantine Arabic to English, and Fongb{\'e} to French. Both pipeline and end-to-end speech translation systems were explored for Tunisian Arabic to English and Fongb{\'e} to French pairs. However, only pipeline approaches were investigated for the North Levantine Arabic{--}English translation direction. All our submissions are based on the usage of pre-trained models that we further fine-tune with the shared task training data."
}