@inproceedings{a50c0f52b758401e869da6e02ce7bb0e,
title = "The SETU-DCU Submissions to IWSLT 2024 Low-Resource Speech-to-Text Translation Tasks",
abstract = "Natural Language Processing (NLP) research and development has experienced rapid progression in the recent times due to advances in deep learning. The introduction of pre-trained large language models (LLMs) is at the core of this transformation, significantly enhancing the performance of machine translation (MT) and speech technologies. This development has also led to fundamental changes in modern translation and speech tools and their methodologies. However, there remain challenges when extending this progress to underrepresented dialects and low-resource languages, primarily due to the need for more data.",
author = "Maria Zafar and Antonio Castaldo and Neha Gajakos and Prashanth Nayak and Rejwanul Haque and Andy Way",
note = "Publisher Copyright: {\textcopyright}2024 Association for Computational Linguistics.; 21st International Conference on Spoken Language Translation, IWSLT 2024 ; Conference date: 15-04-2024 Through 16-04-2024",
year = "2024",
month = sep,
day = "23",
language = "English",
series = "IWSLT 2024 - 21st International Conference on Spoken Language Translation, Proceedings of the Conference",
publisher = "Association for Computational Linguistics (ACL)",
pages = "128--133",
editor = "Elizabeth Salesky and Marcello Federico and Marine Carpuat",
booktitle = "IWSLT 2024 - 21st International Conference on Spoken Language Translation, Proceedings of the Conference",
}