Smart talk An IoT and machine learning based bidirectional assistive communication system for deaf and mute individuals

Communication barriers faced by the hearing and speech-impaired community often limit their social interaction and accessibility. To overcome this challenge, this project presents a sign language recognition and conversion system using Raspberry Pi as the main processor. A USB web camera is employed to capture hand gestures, which are processed using image processing and deep learning techniques to detect and recognize sign language. The recognized signs are then converted into corresponding text and voice output through a speaker. Additionally, a USB microphone is integrated to capture spoken input, which is converted into text and further translated into sign gestures for display. By combining Raspberry Pi, web camera, USB microphone, speaker, and display, this system enables real-time two-way communication between sign language users and non-signers. The proposed solution is portable, cost-effective, and highly beneficial in education, healthcare, and daily communication, fostering inclusivity and accessibility for differently-abled individuals.