Sign Language Translation into Text and Speech using CNN and open CV

Abstract

There are approximately 700,000 deaf and dumb people in this world. Approximately 60% of these people are born deaf and dumb. The language of deaf and dumb that uses body components to convey the message is thought as sign language. Because of the comparative lack of prevalent sign language consumption among the society, deaf and different challenged individuals tend to face problem  on a daily basis. Inability to speak is considered to be true disability. People with this incapacity use completely different modes to speak with others, there are number of ways out there for his or her communication, one such common technique of communication is sign language. Developing sign language application for deaf individuals may be vital, as they?ll be able to communicate easily with even those who don?t recognize sign language actions. Here the job targets to take the fundamental actions in maintaining the verbal gap among traditional individuals and verbally challenged individuals.For them, means of communication becomes very difficult and the only way they can communicate is by means of sign language. Although, a deaf and dumb person might know sign language but the person he wants to communicate with may not know. We want to bridge this gap and provide a way to process sign language and convert it into text and speech with the help of machine learning and neural  networks