Silent Signals AI Power Sign Language Recognization
INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT, 8 (5):
321-328 (October 2024)Abstract
Sign language recognition plays a crucial role in bridging the communication gap between the hearing impaired community and the rest of society. This project focuses on developing a robust system that can accurately recognize and interpret sign language gestures into corresponding text or speech, leveraging computer vision and machine learning techniques. By utilizing deep learning models, particularly convolutional neural networks CNNs for image classification and recurrent neural networks RNNs for sequential gesture recognition, the system aims to achieve real time performance. The proposed system uses a camera to capture hand gestures and processes them to identify individual signs and dynamic sequences, handling variations in lighting, backgrounds, and individual signers. Our model is trained on a diverse dataset of sign language gestures to ensure its adaptability across different users and environments. The ultimate goal of the project is to create a reliable tool that enhances accessibility and fosters more inclusive communication for the deaf and hard of hearing communities. Pratik Kapale | Piyush Kuthe | Kunal Kohale | Pranay Bawanthade | Prof. Suman Sengupta "Silent Signals: AI Power Sign Language Recognization" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-5 , October 2024, URL: https://www.ijtsrd.com/papers/ijtsrd69366.pdf Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/69366/silent-signals-ai-power-sign-language-recognization/pratik-kapale