@inproceedings{das-etal-2025-iwslt,
    title = "{IWSLT} 2025 {I}ndic Track System Description Paper: Speech-to-Text Translation from Low-Resource {I}ndian Languages ({B}engali and {T}amil) to {E}nglish",
    author = "Das, Sayan  and
      Chaudhuri, Soham  and
      Saha, Dipanjan  and
      Das, Dipankar  and
      Bandyopadhyay, Sivaji",
    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-1.23/",
    pages = "245--251",
    ISBN = "979-8-89176-272-5",
    abstract = "Multi-language Speech-to-Text Translation (ST) plays a crucial role in breaking linguistic barriers, particularly in multilingual regions like India. This paper focuses on building a robust ST system for low resource Indian languages, with a special emphasis on Bengali and Tamil. These languages represent the Indo-Aryan and Dravidian families, respectively. The dataset used in this work comprises spoken content from TED Talks and conferences, paired with transcriptions in English and their translations in Bengali and Tamil. Our work specifically addresses the translation of Bengali and Tamil speech to English text, a critical area given the scarcity of annotated speech data. To enhance translation quality and model robustness, we leverage cross-lingual resources and word level translation strategies. The ultimate goal is to develop an end-to-end ST model capable of real-world deployment for under represented languages."
}