Empowering Communication: Converting Sign Language to Text Using CNN Technology

Language plays a crucial role in connecting people within a community. However, individuals who communicate using sign language often face barriers when interacting with those unfamiliar with it, as sign language has its own structure, grammar, and vocabulary that may not be easily understood by others. This presents a significant communication challenge. To address this, we propose a novel solution aimed at creating an autonomous system capable of translating sign language into speech or text in real time. This will be accomplished through the use of deep learning and machine learning algorithms, designed to operate on embedded devices. The dataset for this system has been split into training (90%) and testing (10%) sets. Technologies such as CNN (Convolutional Neural Networks), IoT (Internet of Things), and Python will be utilized to implement this solution.