Isharah dataset
Isharah is a large-scale dataset for Continuous Saudi Sign Language (SSL) recognition and translation. It features over 30,000 video samples signed by deaf and hearing-impaired individuals using smartphones in varied settings.
@article{alyami2025isharah,
title={Isharah: A Large-Scale Multi-Scene Dataset for Continuous Sign Language Recognition},
author={Alyami, Sarah and Luqman, Hamzah and Al-Azani, Sadam and Alowaifeer, Maad and Alharbi, Yazeed and Alonaizan, Yaser},
journal={arXiv preprint arXiv:2506.03615},
year={2025}
}
KArSL dataset
KArSL is the largest video dataset for Word-Level Arabic Sign Language (ArSL). The database consists of 502 isolated sign words collected using Microsoft Kinect V2. Each sign of the database is performed by three professional signers. Each signer repeated each sign 50 times, which resulted in a total of 75,300 samples.
@article{sidig2021karsl,
title={KArSL: Arabic sign language database},
author={Sidig, Ala Addin I and Luqman, Hamzah and Mahmoud, Sabri and Mohandes, Mohamed},
journal={ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP)},
volume={20},
number={1},
pages={1--19},
year={2021},
publisher={ACM New York, NY, USA}
}
ArabSign dataset
ArabSign, a continuous Arabic sign language (ArSL) dataset consists of 9,335 samples representing 50 sentences of Arabic sign language. The dataset’s sentences were performed by 6 signers. Each sentence was repeated by each signer at least 30 times at different sessions. All signers are male with different skin colors. ArabSign dataset was recorded using a Kinect V2 camera that provides three types of information (color, depth, and skeleton joint points) recorded simultaneously for each sentence.
@inproceedings{luqman2023arabsign,
title={ArabSign: A multi-modality dataset and benchmark for continuous Arabic Sign Language recognition},
author={Luqman, Hamzah},
booktitle={2023 IEEE 17th International Conference on Automatic Face and Gesture Recognition (FG)},
pages={1--8},
year={2023},
organization={IEEE}
}
mArSL dataset
mArSL is an isolated Arabic sign language (ArSL) dataset consisting of 6,748 samples representing 50 signs of Arabic sign language. The dataset’s signs were performed by four signers. Each sign was repeated by each signer several times at different sessions. All signers are male with different skin colors. The main focus of this dataset was to record signs that require
@article{luqman2021towards,
title={Towards hybrid multimodal manual and non-manual Arabic sign language recognition: MArSL database and pilot study},
author={Luqman, Hamzah and El-Alfy, El-Sayed M},
journal={Electronics},
volume={10},
number={14},
pages={1739},
year={2021},
publisher={MDPI}
}