Inspiration- People affected by speech impairment can't communicate using hearing and speech, they rely on sign language for communication. Sign language is used among everybody who is speech impaired, but they find a hard time communicating with people which are nonsigners (people aren’t proficient in sign language). So requirement of a sign language interpreter is a must for speech impaired people. This makes their informal and formal communication difficult. There has been favorable progress in the field of gesture recognition and motion recognition with current advancements in deep learning. The proposed system tries to do a real time translation of hand gestures into equivalent English text.
What it does -To develop a system to convert world sign language
into text to help hearing impaired /deaf people while
communicating with the rest of the world.
How we built it- To collect and prepare a data-set.
▪ To select appropriate Machine Learning model.
▪ To train the model.
▪ To test the model.
▪ To create GUI .
Challenges we ran into that would convert sign language to speech and text and vice versa, using natural language processing and computer vision. But he soon ran into a problem that made him realize it would entail a far deeper involvement than he had thought.The big challenge with sign language is that it’s not universal," says Munsamy. It varies from country to country and even in different regions of a large country. American Sign Language (ASL) has gestures associated with words based on how these have evolved over time in the country. In Brazil, the gestures would be different for the same communication.India doesn’t have a standard sign language. This has many ramifications, from lack of access to education for hearing impaired people to barriers in their employment. “If you go to schools for the deaf in India, you will find them mostly using ASL which is single-handed, whereas most variations of Indian sign language are derived from British sign language that uses two hands," points out Munsamy.
Accomplishments that we're proud of Successfully engaging video as an input which can then be processed into useful data in the form of nameable gestures.
What we learned The process of training models and implementing them in a program.
What's next for Sign Language to Text As we improve our data models, additional functionalities and definitions are planned to be added. These could include the implementation of seperate use-cases such as a text to braille or text to morse and vice versa.
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