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@article{187160,
        author = {Prof. Keshav Tambre and Swarup Diwan and Parikshit Doye and Siddharth Dixit and Dnyanesh Bagulkar and Prashansa Dodke},
        title = {ASL Sign Language Recognition System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {3745-3749},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187160},
        abstract = {— This project focuses on designing a solution for the American Sign Language (ASL) recognition system based on software developed on PyCharm. The recognition of ASL gestures uses a combination of machine learning and computer vision techniques. OpenCV is responsible for capturing the videos in real time, whereas TensorFlow with Mediapipe is used for hand tracking and gesture capturing. The model performs recognition of ASL signs with ASL sign dataset and generates text or speech output. The system functions as an interpreter for sign language in real-time and improves the communication of people with hearing impairments. It removes the need for specialized, expensive hardware which makes it more affordable and easier to use. The project goes even further by providing an intuitive graphical user interface so that the user does not have to struggle with interaction. The ASL recognition system may serve education, assistive technology, and real time communications efforts for bridging the gap between the hearing and deaf world.},
        keywords = {ASL, communication, deaf community, gesture recognition, sign language},
        month = {November},
        }