• Spoorti S Aldi
• Omkar Belamkar
• Vishal Nagmule
• Suraj Bhajantri
• Pushpalatha S. Nikkam

Establishing and maintaining communication among individuals is crucial. Specially Abled individuals – people with speech and hearing problems always depend upon communication through sight. This group comprises around 1% of the Indian community. This serves as the primary defense on why adding a framework that could comprehend Indian Sign Language would be helpful to these people. Here, the study suggests a continuous Indian Sign Language gesture detection system that allows motions to be performed with either one or both hands. It understands different motions and stances and outputs the relevant information. The goal to improve the effectiveness of interaction for the public and those with disabilities by presenting a novel approach to real-time hand gesture interpretation. The suggested solution shows promise for improving accessibility and human-computer interaction, with implications for a range of uses beyond helping people with special needs. Using Long Short-Term Memory and MediaPipe, the developed translator was trained to recognize actions and forecast the sign.

Indian Sign Language, Long Short-Term Memory, OpenCV, MediaPipe, Computer Vision, TensorFlow, Recurrent Neural Network.

"A Review on Indian Sign Language Lexical Interpreter", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.k209-k213, March-2024, Available :http://www.jetir.org/papers/JETIR2403A26.pdf

"A Review on Indian Sign Language Lexical Interpreter", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppk209-k213, March-2024, Available at : http://www.jetir.org/papers/JETIR2403A26.pdf