Affiliation:
1. School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India
Abstract
AI-driven speech-to-sign conversion addresses the communication difficulties faced by people with speech impairments. Effective communication is hampered in India, where over 7.45% of the population has speech impairment, by the general public's limited knowledge of sign language. Currently, communication between people with speech impairment and those who do not know sign language is difficult and ineffective. An AI-driven system that instantly converts hand gestures to text and text to sign language aims to improve business communication effectiveness. The existing works on this theme lack the two-way conversion, which makes them less flexible. Finally, the authors' idea aims to close the communication gap that speech-impaired people face and to create a comprehensive two-way converter that can translate text to sign language as well as the other way around, making communication more efficient and available. This model has the potential to greatly enhance interactions, empower people with speech impairments, and promote an inclusive society.