This paper presents a real-time dynamic sign recognition system for English sign language using a support vector machine (SVM) algorithm. The proposed system can detect and recognize signs performed by a signer in real-time, making it suitable for practical applications. The system uses a camera to capture the signer's gestures and then extracts relevant features from the captured images. The extracted features are then classified using an SVM algorithm, which can effectively handle high-dimensional feature vectors and provide accurate classification results. The proposed system is evaluated on a dataset of English sign language gestures and achieves high accuracy in recognizing signs. The results demonstrate the feasibility and effectiveness of the proposed system for real-time sign recognition applications.