Machine Learning-based Sign Language Recognition and Translation System

These are the Indian Sign Language Recognition (SLR) systems, which are essential for bridging the communication gap between the population of people with hearing impairments and those who have lost their capacity to hear. Due to the quick developments in computer vision, deep learning, and machine learning, researchers are very interested in automated sign language gesture detection. These algorithms are able to convert facial expressions, hand gestures, and body language into readable text or speech. The various methods that are present have been mentioned in the review paper to identify sign language, including vision-based, sensor- based systems on upper wearables and techniques. It discusses mainstream machine learning procedures, data, issues, its flaws, and applications. The Indian Sign Language (ISL) is provided with special consideration as it implies the absence of standardised repositories of information and mobile-based real-time systems. Additionally, the research points out gaps in the literature and makes recommendations for future directions in the creation of reliable, long-lasting, multicultural, and mobile-friendly sign language recognition systems.