Published Paper Details:

Sign language is the preferred method of communication for the deaf and hard of hearing community. It is a visual language that uses hand gestures, facial expressions, and body language to convey meaning. Sign language recognition (SLR) is a field of computer science that deals with the development of systems that can automatically recognize and translate sign language into spoken language or text. Sign language recognition systems have the potential to revolutionize the way deaf and hard of hearing people interact with the world around them. They could be used to provide real-time translation services in a variety of settings, such as education, employment, and healthcare. SLR systems could also be used to develop new educational tools and to improve the accessibility of existing technology. Harnessing cutting-edge computer vision and machine learning technologies, this system demonstrates the potential to recognize and interpret a wide array of sign language gestures with remarkable accuracy and efficiency. By employing deep neural networks and sophisticated algorithms, the SLRS aims to convert these gestures into both written text and spoken language, facilitating seamless interaction between deaf individuals and the hearing world.