SPEECH TO SIGN CONVERSION USING NATURAL LANGUAGE PROCESSING

Speech to sign conversion is one essential piece of technology that helps the hearing community and the hearing impaired communicate. This paper presents a novel approach utilizing Natural Language Processing (NLP) techniques for speech to sign conversion. The system that is being suggested leverages advanced NLP algorithms to transcribe spoken language into text, which is thereafter converted to sign language. The process involves several key steps: speech recognition and sign language synthesis. The synthesized sign language gestures are generated based on a comprehensive database of sign language vocabulary and grammar rules. The proposed speech to sign conversion system demonstrates promising outcomes concerning accuracy, efficiency, and usability. By harnessing the power of NLP, this technology possesses the capacity to significantly enhance communication accessibility for the hearing-impaired community, facilitating seamless interaction n a number of fields, such as education and healthcare and social communication.