• Kshitija Satish Patankar
• Shraddha Dattatray Lokhande
• Vaishnavi Rajesh Pathade
• Mrunmayee Deepak Khaire

The communication among a deaf and listening person poses an excessive hassle. Gestural communication is called Sign language. Sign language uses gestures instead of sound to convey meaning, simultaneously combining hand shapes, orientations and movement of the hands and facial expressions to express fluidly a speaker’s thoughts. Signs are used to communicate words and sentences to the audience. The purpose to develop Sign Language Recognition system is to develop an algorithm for recognition of hand gestures with reasonable accuracy, where the input to the pattern recognition system will be given from the hand. It recognizes the pattern and displays the pattern in the form of the text. The information given by camera is collected and stored in the database. The exact meaning of the information is matched with the samples stored previously in the database and is printed. The proposed system is user friendly, as it is easy to use and capable of building efficient and effective human computer interaction.

Sign Language, deaf and mute, image processing, Python, CNN Algorithm, Machine Learning.

"Sign Language Recognition Based On Hand Symbols Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.b753-b755, March-2023, Available :http://www.jetir.org/papers/JETIR2303199.pdf

"Sign Language Recognition Based On Hand Symbols Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. ppb753-b755, March-2023, Available at : http://www.jetir.org/papers/JETIR2303199.pdf