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@article{186518,
        author = {Pratiksha Santosh Shenkar and Ms. Pooja Amin},
        title = {SILENT WHISPERS: A Real-Time Sign Language to Text Translator},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {12},
        number = {no},
        pages = {346-348},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186518},
        abstract = {Individuals who are mute or hard of hearing often struggle to communicate effectively with the broader public, primarily because not everyone understands sign language. This creates a barrier in conveying their thoughts and needs in everyday interactions. The communication gap between sign language users and those unfamiliar poses significant challenges in various aspects of daily life. To address this issue, we proposed to develop a robust and efficient sign language detection system using Python. The objective of this project is to design and implement a machine learning-based system capable of recognizing and translating sign language gestures into written text in real-time. 
It aims to develop a real-time sign language translator that converts sign language gestures into text. Leveraging Python for gesture recognition, Scikit-learn for machine learning, and Jupyter for data analysis and model training, the system provides accurate and efficient translation. The front, designed with React.js and supported by Node.js for development and deployment, offers an intuitive user interface. This integrated approach enhances communication accessibility for the deaf community by providing a seamless and interactive translation experience.},
        keywords = {Real-time translation, Gesture recognition, Sign-Language Detection.},
        month = {},
        }