Abstract: Sign language detection is a revolutionary technology that enables automated recognition and interpretation of sign language gestures, bridging the communication gap between the deaf, dumb and hard of hearing community and rest of society. It developed using machine learning and computer vision techniques. Our innovative approach combines CNN- convolutional neural networks with advanced motion capture technologies to accurately identify a wide array of signs, taking into account that intricacies of hand shapes, movement. Detection: video/image capture >Hand tracking/feature extraction > ML model classification > text/speech output. In our experiments, the detection system demonstrated impressive accuracy rates, and maintained strong performance in real-world situations.

Keywords: CNN (Convolutional Neural Network), ML (Machine learning), Hand tracking.

| DOI: 10.17148/IARJSET.2025.12512