Sign language overcomes the hurdles of communication between special and normal human beings. It is the only mode of communication for hard-of-hearing persons. In this book chapter, an exhaustive survey is done for intersection of intelligent techniques for the development of sign language recognition system. This book chapter details the transformative role of intelligent systems that use cutting-edge algorithms and machine learning techniques to improve the accuracy and efficiency of sign language interpretation. In order to do the thorough survey, relevant papers are extracted from various databases for the period of 2000–2023. This survey facilitates for better understanding of both vision and device-based Sign Language Recognition Systems (SLRS). An exhaustive review of different feature extraction techniques will benefit in choosing an efficient feature extraction algorithm. Further, different classification techniques have been also analyzed for selecting an optimized classification algorithm. This book chapter not only provides a snapshot of the current state of the art but also paves the way for future research directions and highlights the untapped potential inherent in the integration of intelligent systems and SLRS. Essentially, this chapter is expected to serve as a valuable resource for researchers and practitioners’ enthusiasts, offering guidance in the development of intelligent, learning-based systems that hold the promise of revolutionizing communication accessibility for the global deaf and hard-of-hearing community.