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https://doi.org/10.22214/ijraset.2023.49011
Copy DOIPublication Date: Feb 28, 2023 |
Abstract: Sign Language is a non-verbal form of communication that is used to interact with the specially abled. These people have communication barriers when it comes to daily interactions with others who don’t understand sign language. Technological advancements and progress in Machine Learning algorithms have made gesture recognition possible. Sign language is one of the oldest and most natural forms of language for communication, but since most people do not know sign language and interpreters are very difficult to come by, we have come up with a real-time method using neural networks for fingerspelling based on American sign language. In our method, the hand is first passed through a filter and after the filter is applied, the hand is passed through a CNN module which predicts the class of the hand gestures. This literature survey analyses studies based on sign language translator and teaching applications. Conclusions drawn from this literature review could help in creating the perfect application that can make daily communication easy for the specially aided. We plan on providing two modules, one wherein the sign language gestures are converted into text and displayed. The second module is made wherein the text entered is converted into sign language and displayed on the User interface.
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