Dynamic Gesture Recognition Sign Language Interpreter

Abstract—Hand gestures, body postures, and body movements are all part of sign language, which has been the first and millions of people's sole language for a long time. However, for them to interact with others, the other person must also understand these sign language. Everyone is drawn to the digital lifestyle in this ever evolving environment due to technological breakthroughs. As a result, the issue of online communication for deaf and mute individuals who are only accustomed to sign language has emerged. In order to enable the computer to detect, understand, and translate sign language for the necessary task, a sign language recognition system must be developed. This can be accomplished by applying machine learning methods. In this paper we tried to take images of sign language and fed those images to sign language interpreter. Interpreter is designed in python to convert hand sign videos into corresponding text percentage. From that percentage the alphabet will be recognized. Then using Google text to speech it is converted into audio. Thus sign language interpreters developed by us can be used efficiently for dump and deaf people.