<ul><li>Existing Sign Language Learning applications focus on the demonstration of the sign in the hope that the student will copy a sign correctly.</li><li>This paper explores algorithms for real-time, video sign translation, and grading of sign language accuracy for new users.</li><li>The study compares popular algorithms including CNN and 3DCNN on Trinidad and Tobago Sign Language and American Sign Language datasets.</li><li>The 3DCNN algorithm achieved 91% accuracy in the TTSL dataset and 83% accuracy in the ASL dataset, making it the best performing neural network algorithm.</li></ul>

Learning Sign Language Representation using CNN LSTM, 3DCNN, CNN RNN LSTM and CCN TD

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