• Asmita Das
• Pradeep Shastry K S
• B Vedanth
• Gaurav R, Niroshan P
• Dr. M.S Nidhya

This research describes an innovative technique for communicating with people who have speaking and hearing impediments. It discusses a new approach for sign detection and converting signs to text. The developed system can extract indications from video sequences with a minimally congested and dynamic background. It recognizes static and dynamic gestures and extracts the appropriate feature vector for each. Action Recognition using Python is used to classify them. The findings of the experiments show that signs can be segmented satisfactorily against a variety of backdrops, and that gesture and speech recognition can be recognized with reasonable accuracy.

sign-language, sign-language detection, ASL, LSTM, MediaPipe.

"REAL TIME SIGN LANGUAGE RECOGNITION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.275-280, June-2022, Available :http://www.jetir.org/papers/JETIRFM06048.pdf

"REAL TIME SIGN LANGUAGE RECOGNITION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. pp275-280, June-2022, Available at : http://www.jetir.org/papers/JETIRFM06048.pdf