Human Evaluation of English--Irish Transformer-Based NMT

arXiv:2403.02366v1 Announce Type: new
Abstract: In this study, a human evaluation is carried out on how hyperparameter settings impact the quality of Transformer-based Neural Machine Translation (NMT) for the low-resourced English--Irish pair. SentencePiece models using both Byte Pair Encoding (BPE) and unigram approaches were appraised. Variations in model architectures included modifying the number of layers, evaluating the optimal number of heads for attention and testing various regularisation techniques. The greatest performance improvement was recorded for a Transformer-optimized model with a …

abstract architectures arxiv cs.ai cs.cl encoding english evaluation human hyperparameter impact low machine machine translation neural machine translation quality study transformer translation type