Enhancing Language Learning with Real-Time Sign Language Recognition and Feedback
Clapp A. Daniel, Nasr M. Liam, Yasmina Habchi, Saurav Basnet · 2024
Despite the significance of Sign Language education, access to resources with immediate feedback remains a challenge. This study aims to assess the effectiveness of an online learning tool offering real-time video feedback, accessible via basic laptops. Leveraging the capabilities of Google’s Media Pipe software and the project’s robust logic, the prototype aims to provide learners with immediate and accurate feedback, addressing the challenge of access to effective resources for American Sign Language (ASL) education. Focusing on the ASL alphabet, computer-vision based learning tools for static and dynamic signs will be analyzed to explore the tool’s capabilities and limitations.