Hand Detection and Morse Code Translation for Alternative Communication

This paper focuses on developing a real-time Morse code translation system using finger movements captured by a camera and processed with the MediaPipe framework. To enable this, the paper compares the performance of three hand detection algorithms: Yolov5, RetinaNet, and Detectron 2, and identifies MediaPipe as the most effective method for hand tracking. The proposed approach provides a practical and accessible communication method for individuals with speech disorders and opens up new opportunities for improved communication in various settings. The novelty of this work lies in the combination of hand detection algorithms and Morse code translation to develop a robust and efficient communication system for those with speech disorders. Overall, this study highlights the potential of Assistive Speech Technologies in improving communication and promoting inclusion for individuals with speech disorders.