REALTIME SIGN LANGUAGE TO AUDIO & TEXT TRANSLATION USING MACHINE LEARNING

Sign language is the language which is used by the people with speech & hearing disability. It is a technique where people use our hands, palms, fingers to communicate with each other. Generally, it is difficult for the normal people to understand this language. This project deals with the translation of sign language into audio and text. Steps in recognizing and translating the sign language are described in this study. The proposed model is able to recognize a total 30 different signs included 26 alphabets of ASL(American Sign Language) with an average accuracy of 95% in real-time. Real-time sign language recognition without using any external devices, sensors make it easy and comfortable to use. In the proposed model, we have used only a computer with webcam.