Development of a Convolutional Neural Networks Model as a Sign Language Interpreter

This study presents the development of a neural network model as a sign language interpreter. The objective is to facilitate communication between people with hearing disabilities and those who do not master sign language. Using deep learning techniques, the model translates sign language gestures to text in real time. The results show acceptable accuracy and rapid response, significantly improving the interaction and participation of users with hearing disabilities in educational and social environments. This approach promises more fluid and accessible communication, offering a valuable tool for inclusion and collaboration in various everyday situations.