10.25673/122872">


Proceedings of International Conference on Applied Innovation in IT
2025/12/22, Volume 13, Issue 5, pp.369-375

Survey of Sensor-Based Arabic Sign Language Datasets


Ahmed Saleh and Hardik Joshi


Abstract: Sign language is the primary means of communication for the deaf and hard-of-hearing community, representing a linguistic bridge that connects them to society and enables them to express their thoughts and feelings. However, Arabic Sign Language still suffers from a clear lack of scientific research and documented digital databases, which limits the development of automated recognition systems and weakens its integration into modern artificial intelligence applications. This research aims to review and analysis previous studies related to the use of various databases and sensor technologies in Arabic Sign Language recognition, focusing on identifying shortcomings in previous research efforts and proposing methodological approaches to improve data collection and standardize standards among researchers. The study relied on an analytical review of scientific literature to extract conclusions and evaluate the effectiveness of previously developed systems in terms of accuracy and efficiency. The results of the analysis revealed that available databases lack diversity in vocabulary and grammatical structure, which reduces the models' ability to accurately recognize signs. The findings emphasize the importance of developing comprehensive and standardized databases that support the training of intelligent systems and contribute to promoting the integration of deaf people into society and improving their educational and social opportunities.

Keywords: Arabic sign dataset, sign language (SL), recognition gesture, Sensor-Based Recognition.

DOI: 10.25673/122872

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