• Akash Kamble
• Prof. Jitendra Musale
• Rahul Chalavade
• Rahul Dalvi
• Shrikar Shriyal

Sign languages are languages that uses the visual-manual modality to express meaning, instead of just spoken words. It means of communication through facial expressions and bodily movements, especially of the hands and arms, when spoken communication is impossible or not desirable. Sign Language is the methods of communication of deaf and dumb people all over the world. Sign Language to Text Conversion System will be beneficial for helping deaf and dumb persons to communicate with others. The paper proposes a method for an application which would help to convert the Sign language into the text format. With the help of recurrent neural networks and computer vision we can detect hand gestures and give the respective text as an output. We have come up with a system which uses several methods such as using Media Pipe Holistic to place key points on the user, collect Key point values for training and testing, pre-processing data, create labels and features, build and train LSTM neural network.

Hand Gesture, Media Pipe, RNN, machine learning, TensorFlow, OpenCV, Python, etc.

"Design Of Conversion Of Sign Language To Text", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.d291-d294, March-2023, Available :http://www.jetir.org/papers/JETIR2303334.pdf

"Design Of Conversion Of Sign Language To Text", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. ppd291-d294, March-2023, Available at : http://www.jetir.org/papers/JETIR2303334.pdf