Abstract

Millions of individuals with speech and hearing impedances communicate daily through sign language. Hard-of-hearing signal recognition is a distinctive approach to imparting, similar to voice acknowledgment for many people. In this study, we take a gander at the issue of interpreting/changing communication through signing over to a message and propose an exceptional performance given machine learning strategies. We need to lay out a framework that hard-of-hearing individuals might use in their daily existences to advance correspondence and coordinate effort between hard-of-hearing endlessly individuals who aren't prepared in American Sign Language (ASL). To promote a deep learning model for the ASL dataset, we'll involve a Transfer Learning strategy with Data Augmentation.

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