Abstract: SLR seeks to translate gesture-based communication into text or voice to further elaborate on correspondence between the hard of hearing quiet people and other hearing people. Despite this action having a huge cultural impact, it is nonetheless quite difficult due to its complexity and wide variety of hand signals. Existing SLR methods utilize grouping models in consideration of hand-crafted features to handle communication via gestures developments. Lately, it is attempting to gather robust features that can adapt to the wide range of hand movements. We suggest a specific 3D convolutional neural network (CNN) to handle this problem
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DOI:
10.17148/IJARCCE.2024.131114
