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

Adi Rosenthal; Nadav Shaked

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arXiv · 2402.00075

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

Adi Rosenthal·Nadav Shaked

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Abstract

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.

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Adi Rosenthal, Nadav Shaked. 2024-01-30. D-Nikud: Enhancing Hebrew Diacritization with LSTM and Pretrained Models. https://arxiv.org/abs/2402.00075

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