Neural Network based Real Time Sign Language Interpreter for Virtual Meet
D.A. Janeera, K. Mukilan Raja, U K R Pravin, M. K. Prem Kumar · 2021
Due to the Covid-19 pandemic, people were forced to stay home, and most professions switched to Work From Home mode. The world switched to Video Conferencing to stay connected from remote environment. This made Translators unavailable to the hearing impaired. This makes it challenging for deaf-mute people to communicate with other people since there are no credible tools present to translate it real-time in these applications. So, a Translator built within these video conferencing applications would be helpful in communication for these people. Neural Network algorithm is used in our model to predict the signs and translate them. This model is implemented in a video conferencing application which will make the use of the Sign Gesture Translation feature and the other person using the application will receive the translation in text on a real time basis.