IoT-Enabled Sign Language to Speech Converter for Enhanced Communication

This paper describes a novel sign language recognition system which translates gestures made by someone who is deaf or hard of hearing into speech. Privacy Traditional sign language recognition systems fail to deliver real-time interaction and customization that are crucial for a great experience. Furthermore, the system uses adaptive learning algorithms to make for a personalized experience that gets better at recognizing your sign over time. The technology is constructed from a union of high-resolution cameras and accelerometers for the capture gestures, using sophisticated image processing & machine learning techniques to perceive and translate these movements into oral language. We describe the system design and implementation including evaluation, which shows that the proposed approach is both effective based on extensive testing as well as user trials. Our results significantly improved the efficiency, accuracy and user satisfaction of communication (real world applicability) Therefore, for inclusive communication this paper has magnificently filled the communication gap among sign language users, becoming a reinforcement in body language understanding.