• Shaheen Tabassum
• Raghavendra R

Sign language is a shape of transmission that use quite a few hand gestures and motions to deliver information. It's possible that deciphering these movements is a pattern recognition difficulty. Humans employ a variety of gestures and actions to send various signals to one another. This project is a framework for a human-computer interface that can recognize movements in sign language and provide a written output that conveys the gesture's meaning. The suggested system would use convolutional neural networks and long short term memory networks to recognize and learn gestures. This will assist to reduce the communication barrier.

Feature Extraction and Representation, Artificial Neural Networks, Convolutional Neural Networks, Tensor Flow, Keras, OpenCV.

"Sign Language Recognition and Converting into Text: A Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 3, page no.b664-b667, March-2022, Available :http://www.jetir.org/papers/JETIR2203185.pdf

"Sign Language Recognition and Converting into Text: A Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 3, page no. ppb664-b667, March-2022, Available at : http://www.jetir.org/papers/JETIR2203185.pdf