Automated Sign Language Interpreter Using Data Gloves

Communication plays a very important role in the everyday life of human beings. Keeping this in mind, this project aims to aid the deaf and the dumb in communicating with others. Sign language is used for this form of communication and it is an incredible advancement that has grown over the years. This project helps in improving the communication with the deaf and the dumb using flex sensor technology. We convert the sign language so that it is understood by common people and will help them to communicate without any barriers. The main purpose of this project is to eliminate the barrier between the deaf and dumb and the others using an automated system to recognize the hand gestures and interpret them appropriately. The system uses a combination of sensors fixed onto a glove to capture various sign gestures. The sensor values for these signs are then recorded by the Arduino and processed using K nearest neighbor machine learning algorithm. There are many challenges that come with the usage of the sign language. Not everyone knows how to interpret the sign language. Hence, we use a sensor based glove to overcome this issue. Currently, the system is able to successfully classify 21 letters and basic phrases with an accuracy of 93% for the chosen value of K in the nearest neighbor algorithm.