Gestures are basically the physical action form performed by a person to convey some meaningful information. Gestures area powerful means of communication among humans. The Sign language is very important for people who have hearing and speaking deficiency generally called Deaf and Mute. It is the only mode of communication for such people to convey their messages and it becomes very important for people to understand their language. The aim of our project is to implement a system that will help deaf and dumb people to communicate with others. It recognises the hand gestures with highest accuracy and in least possible time and translates them into corresponding voice so that the people who don't know the sign language, can understand the meaning. It is implemented in MATLAB and uses Eigen Value Weighted Euclidean Distance Based Classification Technique. The output is the sound corresponding to the recognised sign. Keywords: Sign Language, Feature Extraction, Sign Recognition, PCA.