AD-RDAT

Implementation of paper "Improving Arabic Diacritization with Regularized Decoding and Adversarial Training" at ACL-2021

Citation

@inproceedings{qin-etal-2021-improving,
    title = "Improving Arabic Diacritization with Regularized Decoding and Adversarial Training",
    author = "Qin, Han and Chen, Guimin and Tian, Yuanhe and Song, Yan",
    booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
    month = aug,
    year = "2021",
    address = "Online",
    pages = "534--542",
}

Requirements

Our code works with python 3.8 and requires the following packages: sklearn, pytorch.

It also require the PyTorch version of pre-trained language models: multi-lingual BERT and AraBERT.

Usage

See the commands in run.sh to train a model on the small sample data.