Datasetpublic

IbrahimAmin/arz-en-parallel-corpus

Egyptian Arabic - English Parallel Corpus 🇪🇬✨🇬🇧 Dataset Description This dataset is a cleaned and filtered merge of multiple Egyptian Arabic - English parallel corpora, containing ~27,000 aligned sentence pairs. It’s designed for researchers and developers working on machine translation, speech translation, and other NLP tasks involving Egyptian Arabic and English. Sources 📚 This dataset integrates and refines data from the following publicly… See the full description on the dataset page: https://huggingface.co/datasets/IbrahimAmin/arz-en-parallel-corpus.

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Dataset Card

Egyptian Arabic - English Parallel Corpus 🇪🇬✨🇬🇧

Dataset Description

This dataset is a cleaned and filtered merge of multiple Egyptian Arabic - English parallel corpora, containing ~27,000 aligned sentence pairs. It’s designed for researchers and developers working on machine translation, speech translation, and other NLP tasks involving Egyptian Arabic and English.

Sources 📚

This dataset integrates and refines data from the following publicly available sources:

Languages 🗣️

—Egyptian Arabic (arz)
—English (en)

Size 📏

~27,000 parallel sentence pairs

Split	Number of Samples
Train	25,000
Test	1,851
Total	26,851

Applications 🚀

Ideal for:

—Machine Translation (MT)
—Speech Recognition (ASR) with translation support

Preprocessing 🧹

—Removed rows with only numbers or non-informative tokens.
—Removed special tags like [HES], [LAUGHTER], and any content inside brackets (e.g., [tag]) while avoiding extra spacing.
—Filtered out missing or empty translations.
—Eliminated duplicate samples based on full row content.
—Shuffled the dataset to randomize sample order.

Usage Example

python

from datasets import load_dataset

dataset = load_dataset("IbrahimAmin/arz-en-parallel-corpus")
print(dataset['train'][0])

License 📄

MIT License — freely usable for research and commercial purposes

👏 Acknowledgement

Special thanks to **Hesham Haroon**, the **arbml team** and **Injy Hamed** for creating and sharing these valuable datasets.

Citation 📝

If you use this dataset, please cite:

bibtex

@inproceedings{hamed-etal-2022-arzen,
  title     = {ArzEn-ST: A Three-way Speech Translation Corpus for Code-Switched Egyptian Arabic-English},
  author    = {Hamed, Injy and Habash, Nizar and Abdennadher, Slim and Vu, Ngoc Thang},
  booktitle = {Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP)},
  pages     = {119--130},
  year      = {2022},
  address   = {Abu Dhabi, United Arab Emirates (Hybrid)},
  publisher = {Association for Computational Linguistics},
  url       = {https://aclanthology.org/2022.wanlp-1.12},
  doi       = {10.18653/v1/2022.wanlp-1.12}
}

bibtex

@article{al-sabbagh-2024-arzen-multigenre,
  title     = {ArzEn-MultiGenre: An aligned parallel dataset of Egyptian Arabic song lyrics, novels, and subtitles, with English translations},
  author    = {Al-Sabbagh, Rania},
  journal   = {Data in Brief},
  volume    = {54},
  pages     = {110271},
  year      = {2024},
  publisher = {Elsevier},
  doi       = {10.1016/j.dib.2024.110271},
  url       = {https://www.sciencedirect.com/science/article/pii/S2352340924002403}
}

bibtex

@misc{amin2025arzenparallel,
  author       = {Amin, Ibrahim},
  title        = {Egyptian Arabic - English Parallel Corpus},
  year         = {2025},
  url          = {https://huggingface.co/datasets/IbrahimAmin/arz-en-parallel-corpus},
  note         = {MIT License. Curated and cleaned from multiple public datasets.}
}