Survey on Gestures Translation System for Hearing Impaired People in Emergency Situation using Deep Learning Approach

Stone-deaf persons utilize gesture language as a form of communication. Disabled As a kind of non-verbal communication, individuals use sign language movements to convey their feelings and ideas to others. Communicating with someone who has hearing impairment is challenging. It is challenging for non-deaf as well as mute individuals to comprehend the hand motion sign language used by deaf and mute individuals to communicate. As a consequence, it is necessary to develop technologies that can identify countless signs and transmit the knowledge to person in the street. For medical and legal visits, in addition to educational and training sessions, professional sign language experts are needed because these regular people have trouble comprehending their facial expressions. Recently, there has been a growing demand for such services. Other services like video remote human interpretation, which requires a high-speed internet connection, have also been developed, offering a simple gesture recognition interpretation service with limitations. To address this issue, machine learning can be applied to analyze the user's hand using finger detection. Deep learning approaches have significantly improved the several algorithms that have been put forth by numerous academics over the past few years. This study has analysed the deep learning-based vision-related models for gesture recognition.