Abstract- Sign language is a vital mode of communication for individuals with hearing impairments. However, the communication gap between the deaf community and the hearing world remains a significant challenge. To bridge this gap, sign language recognition systems have emerged as a powerful tool. This project paper presents a comprehensive study on the development of a sign language recognition system that utilizes computer vision and machine learning techniques. The system aims to accurately recognize and interpret sign language gestures, enabling effective communication between deaf individuals and the broader society. The paper discusses the methodology, implementation, challenges, and future directions of the project.
Keywords— Sign Language, ASL, Hearing disability, Convolutional Neural Network (CNN), Computer Vision, Machine Learning, Gesture recognition, Sign language recognition, Hue Saturation Value algorithm
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DOI:
10.17148/IJARCCE.2023.125196
[1] Dr. Shilpa R, Pratheek Gowda D J, Shamanth T N, Sandeep B, K S Shamantaka, "Sign Language Recognition System," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2023.125196
