# D-Nikud: Enhancing Hebrew Diacritization with LSTM and Pretrained Models

arXiv: https://arxiv.org/abs/2402.00075 · HTML: https://mlsanity.com/paper/2402.00075/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 7 references that are in the map.
- First posted on arXiv 30 Jan 2024.

## Builds on (most cited first, 1 of 1)

- [Breaking Character: Are Subwords Good Enough for MRLs After All?](https://mlsanity.com/paper/2204.04748/) (2022)

## Abstract (arXiv)

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.