Understanding Saudi Arabic Sign Language Gestures

In Saudi Arabia, a nation rich in traditions and diverse cultures, Saudi Sign Language (SSL) serves as a crucial communication method for the deaf community, embodying both the Kingdom's heritage and adaptability.

The Origin of Saudi Sign Language (SSL) developed naturally within deaf communities in Saudi Arabia. Initially based on informal sign systems used in families and local settings, SSL evolved into a recognized language with unique grammar, syntax, and regional variations.

Government Acknowledgment and Support Efforts:  to formally recognize and support SSL have increased, with the Ministry of Education and other institutions promoting SSL as a cultural and linguistic asset. Steps have been taken to integrate SSL into educational settings, providing resources and support for deaf students.

Usage and Community Influence: Estimating the number of SSL users is challenging, but it remains a primary communication tool for many deaf individuals in Saudi Arabia. SSL plays a vital role in education, employment, and social integration, fostering a sense of belonging and community among deaf Saudis.

Noteworthy Aspects:

1.Cultural Sensitivity: SSL reflects Saudi cultural nuances and traditions, preserving the Kingdom’s heritage within the deaf community.

2.Advocacy and Awareness: Advocacy groups have been instrumental in raising awareness about SSL, pushing for its recognition, and promoting equal opportunities for the deaf.

3.Technology and Modernization: Modern technology, including video communication and online resources, has enhanced the accessibility and preservation of SSL. Additionally, the use of clearer images and datasets, as seen in studies and references, has facilitated better understanding and documentation of SSL.

 Comparing All References: The references provided contribute significantly to the creation of a reference image for creating dataset for SSL.The design and development of a system for automatic translation of Saudi Arabic sign language to text highlight the use of clearer images to improve accuracy. I planned to capture images with my hand cross checking below references and make this custom reference images.These images will be base for extracting data points from media pipe library.

Own dataset reference image for SSL:

 

  

Reference : 

 

[1] A. M. Ahmed, R. A. Alez, M. Taha, and G. Tharwat, “Propose a New Method for Extracting Hand using in the Arabic Sign Language Recognition (Arslr) System,” Int. J. Eng. Res. Technol., vol. V4, no. 11, Nov. 2015, doi: 10.17577/IJERTV4IS110005.
 
[2] M. Ismail, S. Dawwd, and F. Ali, “Static hand gesture recognition of Arabic sign language by using deep CNNs,” Indones. J. Electr. Eng. Comput. Sci., vol. 24, p. 178, 2021, doi: 10.11591/ijeecs.v24.i1.pp178-188.

[3] “Arabic Sign Language Recognition System on Smartphone Semantic Scholar - Online Store.” https://goodayzsk.shop/product_details/24144586.html (accessed Jul. 05, 2024).

[4] A. H. Al-Obodi, A. M. Al-Hanine, K. N. Al-Harbi, M. S. Al-Dawas, and A. A. Al-Shargabi, “A Saudi Sign Language Recognition System based on Convolutional Neural Networks,” Int. J. Eng. Res. Technol., vol. 13, pp. 3328–3334, 2020, doi: 10.37624/IJERT/13.11.2020.
3328-3334.



 


 

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