Sign language plays a crucial role in facilitating communication within the hearing-impaired community, yet it often poses a challenge as a communication barrier with the broader society. Recent technological and Artificial Intelligence (AI) advancements present an opportunity to bridge this communication gap effectively. This research delves into the essential components of developing a Sign Language Recognition system, exploring aspects such as sign-capturing techniques, selection of sign datasets, preprocessing methods, and integrating a deep learning module featuring both CNN and CNN-SVM modules.