Investigating Neural Machine Translation for Low-Resource Languages: Using Bavarian as a Case Study

arXiv:2404.08259v1 Announce Type: new
Abstract: Machine Translation has made impressive progress in recent years offering close to human-level performance on many languages, but studies have primarily focused on high-resource languages with broad online presence and resources. With the help of growing Large Language Models, more and more low-resource languages achieve better results through the presence of other languages. However, studies have shown that not all low-resource languages can benefit from multilingual systems, especially those with insufficient training and evaluation data. …

abstract arxiv case case study cs.cl human language language models languages large language large language models low machine machine translation neural machine translation performance progress resources studies study translation type