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In the current fast-moving world, human-computer- interactions (HCI) is one of the main contributors towards the progress of the country. Since the conventional input devices limit the naturalness and speed of human-computer- interactions, Sign Language recognition system has gained a lot of importance. Different sign languages can be used to express intentions and intonations or for controlling devices such as home robots. The main focus of this work is to create a vision based system, a Convolutional Neural Network (CNN) model, to identify six different sign languages from the images captured. The two CNN models developed have different type of optimizers, the Stochastic Gradient Descent (SGD) and Adam.