Real Time Hand Sign Language Recognition Using Deep Learning: A Robust and Efficient Model for Improved Communication Accessibility

People with special needs shouldn't be left behind in a world where technology is developing quickly. Deaf people may communicate themselves beautifully using sign language, but sadly, it can be challenging for others to comprehend. Our state-of-the-art computer vision system enters the picture here. We have developed a technology that can properly interpret hand movements in real time using neural networks and sophisticated machine learning algorithms. Our system achieves astounding accuracy rates of 90% by using the most recent development libraries, including Tensorflow, Python, and OpenCV. With the help of this ground-breaking technology, we are removing obstacles to communication and enhancing accessibility for everyone. We are trying to emphasize on the impact of the technology on accessibility and inclusivity for all individuals, including those with special needs. The system's ability to interpret sign language in real-time can remove communication barriers and enable deaf individuals to communicate effectively with others.