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							Real-Time AI-Powered Sign Language Translation System for Inclusive Communication
Abstract
In order to address communication barriers between hearing and deaf people, this paper describes the creation of an AI- based application that enables real-time translation of sign language into speech and text. Convolutional Neural Networks (CNNs), Media Pipe for real-time gesture recognition, an easy-to-use user interface, and a feedback loop for ongoing enhance- ment are all features of the system. The suggested system improves accessibility and inclusivity in fields like public ser- vices, healthcare, and education. Future developments will include support for more sign languages and integration with wearable technology.
References
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Y. Hu and Y. Wang, "Deep Learning for Sign Language Recognition," IEEE Trans. Human-Machine Systems, 2019.
RWTH-PHOENIX-Weather 2014T Dataset.
A. Ng, "Specialization in Deep Learning," Coursera.
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