Machine Translation
Machine translation (MT) aims to automatically translate text between languages, with current research heavily focused on leveraging large language models (LLMs) and exploring various architectures like encoder-decoder and decoder-only models. Key areas of investigation include improving translation quality, particularly for low-resource languages and specialized domains like medicine, mitigating biases (e.g., gender bias), and enhancing evaluation methods beyond simple correlation with human judgments. These advancements have significant implications for cross-cultural communication, information access, and the development of more equitable and effective multilingual technologies.
Papers
Transformers for Low-Resource Languages:Is F\'eidir Linn!
Séamus Lankford, Haithem Afli, Andy Way
adaptNMT: an open-source, language-agnostic development environment for Neural Machine Translation
Séamus Lankford, Haithem Afli, Andy Way
Human Evaluation of English--Irish Transformer-Based NMT
Séamus Lankford, Haithem Afli, Andy Way