Sign Language Recognition: Advancing Human-Computer Interaction through Machine Learning

Sign language is an essential tool for communication among individuals with hearing impairments.The recent progress in computer vision and machine learning has significantly advanced the development of systems that recognize and interpret sign language, contributing to their evolution.These systems play a vital role in bridging communication gaps by automatically identifying and interpreting sign language gestures, facilitating seamless and effective communication. This paper reviews and analyzes sign language recognition systems, covering methodologies and potential applications, including data collection, hand and gesture tracking, feature extraction, and classification algorithms. The goal is to promote inclusivity and equal opportunities by fostering communication between sign language users and the broader community.