D-Nikud: Enhancing Hebrew Diacritization with LSTM and Pretrained Models
Adi Rosenthal Nadav Shaked
D-Nikud, a novel approach to Hebrew diacritization that integrates the
strengths of LSTM networks and BERT-based (transformer) pre-trained model.
Inspired by the methodologies employed in Nakdimon, we integrate it with the
TavBERT pre-trained model, our system incorporates advanced architectural
choices and diverse training data. Our experiments showcase state-of-the-art
results on several benchmark datasets, with a particular emphasis on modern
texts and more specified diacritization like gender.