Breaking Barriers: Sign Language-to-Text Transformation in the Digital Era

This review paper investigates the evolving field of sign language-to-text conversion (SLTC), exploring the remarkable technological strides, challenges, and profound impact on communication accessibility on behalf of the community of deaf and hard of hearing (DHH). The paper also addresses the user experience aspects of SLTC systems, discussing their user-friendly design, interface considerations, and the incorporation of feedback mechanisms for continuous improvement. Furthermore, it presents findings from user testing, demonstrating the reliability and practicality of SLTC in various communication scenarios. The accuracy of SLTC systems can range from around 70 to 90% or more, depending on factors such as the quality and size of the dataset used for training, the complexity of the sign language, the effectiveness of recognition algorithms, and the robustness of translation models.