There are several obstacles when communicating with those who are deaf or hard of hearing, but sign language has become an essential tool. It is an excellent tool that helps people with speech and hearing impairments convey their ideas and feelings. This encourages less complicated integration with the outside environment. But because sign language has its own set of difficulties, its simple construction is insufficient. It might be difficult to interpret gestures for people who are not familiar with sign language or who speak a different sign language. Thankfully, new developments in technology have brought about a number of methods for automating the recognition of sign movements, which provide encouraging alternatives. This invention has the potential to close the long- standing communication gap considerably. In this work, we presented the usage of our exclusive dataset to identify hand motions. Our research project uses a webcam to allow users to take pictures of their hand gestures. The system's goal is to anticipate and show the name that corresponds to the image that was taken. Convolutional Neural Networks (CNNs) are used for image training and classification, with computer vision aiding in the image collection and capture process.