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Project demonstrates a sign language translation system in real time, suggesting improved communication accessibility for hearing- and speech-impaired individuals.
The project presents a Sign Language Translator using deep learning that helps hearing- and speech-impaired people communicate easily with others. It uses CNN and LSTM models to recognize hand gestures from a camera and convert them into text or speech in real time. The system is cost-effective, accurate (around 95–97%), and does not require special hardware, making communication more accessible and inclusive.
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T et al. (2026) studied this question.
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