Hand Sign To Text Conversion Using ML

Hand sign language is an essential form of communication for individuals with hearing impairments. However, the language barrier between sign language users and non-sign language users often hinders effective communication. This paper presents a novel approach to bridge this gap by developing a system that translates hand signs into text using machine learning techniques, augmented with a built-in voice output. The system includes a voice output feature that is built-in to improve the user experience. Real-time communication is made possible once the hand sign has been identified and translated into text by the system, which also produces a corresponding audio output. Text-to-speech algorithms are used to synthesise the voice output, which gives non-sign language users a spoken version of the sign language message.