To Review on Speech-to-Sign Language Conversion System Using Natural Language Processing

The project aims to bridge the communication gap between hearing individuals and the deaf community by developing a speech-to-sign language conversion system. This system transforms spoken language into corresponding sign language gestures, enabling real-time, inclusive communication. Leveraging advanced speech recognition algorithms and natural language processing (NLP), the spoken input is converted into text. The text is then analysed, segmented into meaningful components, and mapped to sign language gestures displayed as animations or visuals. This approach prioritizes accessibility and ease of use, ensuring that individuals with hearing impairments can participate seamlessly in conversations. The system’s modular design allows adaptability for sign languages and continuous improvement through machine learning techniques. By combining cutting-edge technology with a user-centric focus, this project provides an innovative tool for enhancing inclusivity in communication.