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@article{161607,
        author = {Tanmay Zade and Arati Deshpande and Aditya Zite and Gaurav Zanwar and Rohan Zombade and Harsh Maske and Vaibhav Zendage},
        title = {SWARAYANTRA - A Gesture Language Translator},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {6},
        pages = {411-413},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=161607},
        abstract = {The system is proposed to develop a sign language translator using raspberry pi. For the purpose of recognizing and interpreting sign language gestures, this system employs computer vision and machine learning algorithms. The raspberry pi board is used as the main processing unit, and the system includes a camera for capturing images of the signer’s hand gestures. To identify the sign language gestures in the photos, OpenCV and machine learning methods are used. The system then translates the gesture into text, allowing individuals who do not understand sign language to communicate with signers. The proposed system has the potential to facilitate communication and accessibility for individuals with hearing impairments. The project aims to demonstrate the capabilities of raspberry pi as a cost-effective solution for developing assistive technologies for people with disabilities. Future work includes improving the recognition system's accuracy and developing a user-friendly interface to make the system more accessible to a wider audience.},
        keywords = {},
        month = {},
        }