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@article{187048,
        author = {Syna Bernard and Sujal Bhogade and Prof. Rinku Badgujar},
        title = {Sign Language to Text Converter},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {7646-7653},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187048},
        abstract = {Communication is a fundamental aspect of human interaction, yet individuals with hearing and speech impairments often face barriers in expressing themselves to those unfamiliar with sign language. This project presents a Sign Language to Text Converter designed to bridge this communication gap by translating hand gestures into readable text in real time. The system utilizes a camera to capture sign gestures, which are then processed using image recognition and machine learning algorithms to identify corresponding alphabets or words. The recognized gestures are displayed as text on the screen, enabling seamless interaction between sign language users and non-signers.
The proposed model employs advanced computer vision techniques for hand segmentation, contour detection, and feature extraction, followed by classification through a Convolutional Neural Network (CNN) trained on a diverse dataset of sign language gestures. By implementing real-time frame processing and optimized inference, the system ensures minimal latency and high recognition accuracy across varying lighting and background conditions. Furthermore, the application integrates an intuitive graphical interface that allows users to visualize continuous text output, improving usability and accessibility.
The project emphasizes affordability, scalability, and ease of deployment, making it suitable for educational, workplace, and public communication environments. Overall, this research contributes toward promoting inclusivity and social integration through a reliable and efficient sign language translation system powered by artificial intelligence.},
        keywords = {Sign Language, Gesture Recognition, Image Processing, Machine Learning, Computer Vision, Real-Time Translation, Accessibility, Human-Computer Interaction, Inclusivity.},
        month = {November},
        }