Sign Language Recognition-Based Machine Learning Model for Hearing Disabilities Person

The Sign Language Detection System is a revolutionary application that leverages the power of machine learning, deep learning, and computer vision to detect and interpret sign language gestures in real time. Sign language is a vital means of communication for individuals with hearing disabilities, allowing them to express their thoughts, needs, and emotions. However, there is often a communication gap between individuals who use sign language and those who do not understand it. The proposed system aims to bridge this gap by providing an automated and accurate solution for real-time sign language interpretation. Sign language interpretation has traditionally relied on human interpreters, which poses several challenges such as availability, cost, and accuracy. These limitations can restrict effective communication in various settings, including educational institutions, healthcare facilities, public spaces, and social interactions. Furthermore, the dependence on human interpreters may lead to delays in communication, especially in situations where immediate interpretation is crucial. This chapter aims to develop an accurate sign language recognition machine learning model that enables real-time sign language interpretation. This model improves communication accessibility and it is also promoting technological advancements in sign language interpretation.