Enhancing Neural Machine Translation of Low-Resource Languages: Corpus Development, Human Evaluation and Explainable AI Architectures

arXiv:2403.01580v1 Announce Type: new
Abstract: In the current machine translation (MT) landscape, the Transformer architecture stands out as the gold standard, especially for high-resource language pairs. This research delves into its efficacy for low-resource language pairs including both the English$\leftrightarrow$Irish and English$\leftrightarrow$Marathi language pairs. Notably, the study identifies the optimal hyperparameters and subword model type to significantly improve the translation quality of Transformer models for low-resource language pairs.
The scarcity of parallel datasets for low-resource languages can hinder MT development. …

abstract architecture architectures arxiv cs.ai cs.cl current development english evaluation explainable ai human landscape language languages low machine machine translation neural machine translation research standard transformer transformer architecture translation type