Word Recognition from Sign Language using Deep Learning

In the pursuit of fostering better communication between the Deaf community and the public, the Word Recognition initiative employs Convolutional Neural Networks (CNNs). This effort introduces an innovative approach to interpret sign language gestures and convert them into written text. Utilizing the spatial information extracted by CNNs, our model excels in understanding the intricate hand movements and subtle gestures inherent in sign language. Through the application of advanced deep learning techniques, the system demonstrates its capacity to provide real-time and accurate translations of sign language into easily understandable text. Empirical findings from a diverse dataset of sign language gestures underscore the system's efficiency, precision, and speed. The successful integration of the CNNbased Word Recognition System marks a significant advancement in promoting inclusivity and accessibility, facilitating seamless communication between the Deaf community and the broader population.