Mobile-Based Hausa Sign Language (hsl) Learning Application

Sign language serves as a crucial communication medium for individuals with hearing impairments, enabling them to engage effectively with society. However, Hausa Sign Language (HSL) remains significantly underrepresented in digital advancements compared to other widely recognized sign languages. This paper introduces a mobile-based learning application specifically designed to facilitate the learning, preservation, and accessibility of HSL. The application integrates an interactive educational framework that incorporates multimedia learning materials alongside an adaptive quiz system aimed at reinforcing comprehension and retention of sign language concepts. The methodological approach adopted in this study encompasses system analysis, application design, iterative development, and user-cantered evaluation. Results from preliminary user testing indicate that the mobile application significantly enhances HSL acquisition by fostering a more engaging and structured learning environment. The findings underscore the potential of mobile technology in bridging accessibility gaps for the hearing-impaired community. Future developments will focus on expanding the application’s lexicon, improving the user interface, and incorporating machine learning-driven sign recognition to further enrich the user experience and improve real-time feedback mechanisms. Additionally, further research into the integration of artificial intelligence (AI) and deep learning models for real-time sign interpretation and predictive text-to-sign conversion will be explored.