Neural Arabic Text Diacritization: State of the Art Results and a Novel Approach for Machine Translation
Ali Fadel, Ibraheem Tuffaha, Bara’ Al-Jawarneh, Mahmoud Al-Ayyoub
Abstract
In this work, we present several deep learning models for the automatic diacritization of Arabic text. Our models are built using two main approaches, viz. Feed-Forward Neural Network (FFNN) and Recurrent Neural Network (RNN), with several enhancements such as 100-hot encoding, embeddings, Conditional Random Field (CRF) and Block-Normalized Gradient (BNG). The models are tested on the only freely available benchmark dataset and the results show that our models are either better or on par with other models, which require language-dependent post-processing steps, unlike ours. Moreover, we show that diacritics in Arabic can be used to enhance the models of NLP tasks such as Machine Translation (MT) by proposing the Translation over Diacritization (ToD) approach.- Anthology ID:
- D19-5229
- Volume:
- Proceedings of the 6th Workshop on Asian Translation
- Month:
- November
- Year:
- 2019
- Address:
- Hong Kong, China
- Editors:
- Toshiaki Nakazawa, Chenchen Ding, Raj Dabre, Anoop Kunchukuttan, Nobushige Doi, Yusuke Oda, Ondřej Bojar, Shantipriya Parida, Isao Goto, Hidaya Mino
- Venue:
- WAT
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 215–225
- Language:
- URL:
- https://aclanthology.org/D19-5229
- DOI:
- 10.18653/v1/D19-5229
- Cite (ACL):
- Ali Fadel, Ibraheem Tuffaha, Bara’ Al-Jawarneh, and Mahmoud Al-Ayyoub. 2019. Neural Arabic Text Diacritization: State of the Art Results and a Novel Approach for Machine Translation. In Proceedings of the 6th Workshop on Asian Translation, pages 215–225, Hong Kong, China. Association for Computational Linguistics.
- Cite (Informal):
- Neural Arabic Text Diacritization: State of the Art Results and a Novel Approach for Machine Translation (Fadel et al., WAT 2019)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/D19-5229.pdf
- Code
- AliOsm/shakkelha + additional community code
- Data
- Arabic Text Diacritization