SIGNEASE: AI-Driven American Sign Language Interpretation System

Sign Language Recognition has grown to be increasingly important as a mean to improve the access and effective communication for the hearing impaired through Human Computer Interaction (HCI). This paper presents a hybrid approach, unifying deep learning with graph theory, that effectively recognizes sign language gestures in terms of recent state-of-the-art advances in artificial intelligence. Such being applied to a large dataset thus proves to yield quite noteworthy improvements both in terms of recognition accuracy and computational efficiency that can be gained. For these reasons, this method is established to be a competitive solution in the field.