@inproceedings{ahmadi-etal-2025-parme,
    title = "{PARME}: Parallel Corpora for Low-Resourced {M}iddle {E}astern Languages",
    author = {Ahmadi, Sina  and
      Sennrich, Rico  and
      Karami, Erfan  and
      Marani, Ako  and
      Fekrazad, Parviz  and
      Baghban, Gholamreza Akbarzadeh  and
      Hadi, Hanah  and
      Heidari, Semko  and
      Dogan, Mah{\^i}r  and
      Asadi, Pedram  and
      Bashir, Dashne  and
      Ghodrati, Mohammad Amin  and
      Amini, Kourosh  and
      Ashourinezhad, Zeynab  and
      Baladi, Mana  and
      Ezzati, Farshid  and
      Ghasemifar, Alireza  and
      Hosseinpour, Daryoush  and
      Abbaszadeh, Behrooz  and
      Hassanpour, Amin  and
      Hamaamin, Bahaddin Jalal  and
      Hama, Saya Kamal  and
      Mousavi, Ardeshir  and
      Hussein, Sarko Nazir  and
      Nejadgholi, Isar  and
      {\"O}lmez, Mehmet  and
      Osmanpour, Horam  and
      Ramezani, Rashid Roshan  and
      Aziz, Aryan Sediq  and
      Salehi, Ali  and
      Yadegari, Mohammadreza  and
      Yadegari, Kewyar  and
      Roodsari, Sedighe Zamani},
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingestion-acl-25/2025.acl-long.1451/",
    pages = "30032--30053",
    ISBN = "979-8-89176-251-0",
    abstract = "The Middle East is characterized by remarkable linguistic diversity, with over 400 million inhabitants speaking more than 60 languages across multiple language families. This study presents a pioneering work in developing the first parallel corpora for eight severely under-resourced varieties in the region{--}PARME, addressing fundamental challenges in low-resource scenarios including non-standardized writing and dialectal complexity. Through an extensive community-driven initiative, volunteers contributed to the creation of over 36,000 translated sentences, marking a significant milestone in resource development. We evaluate machine translation capabilities through zero-shot approaches and fine-tuning experiments with pretrained machine translation models and provide a comprehensive analysis of limitations. Our findings reveal significant gaps in existing technologies for processing the selected languages, highlighting critical areas for improvement in language technology for Middle Eastern languages."
}