Published Paper Details:

Human beings can communicate with one another via natural language channels including words and writing, or through body language (gestures) like hand gestures, head gesticulations, facial expressions, lip motion, and so forth. Learning to read and write in normal language is essential but knowing sign language is equally essential. Individuals who are partially deaf rely on sign language as their primary mode of communication. People who have hearing impairments have difficulty communicating with those who do not have hearing issues if they do not have access to a translator [1]. This is why the deaf community will benefit greatly from a technology that understands sign language especially hand gestures. Even though mobile technology is rapidly evolving and becoming incredible, there has been little technological advancement and development for artificial intelligence voice-based smart devices that can assist deaf people in understanding and responding to their body language. When combined with learning algorithms, ubiquitous sensing may be used to integrate all of the body language information. As with spoken language, body language has a variety of libraries and each communication is distinct [1]. With my technology, each user can program their device to detect and comprehend their hand gestures, allowing it to recognize and interpret those signals into a voice. It provides users with full command over their sign language library as well as their spoken communication, making it helpful for anybody who has difficulty hearing or speaking. Studies to investigate ways of bridging this breakdown in communication for the deaf have been in progress, with more to come. There are now available stand-alone tools and apps that may aid in the interaction among people who are profoundly deaf [2]. This is why this research aims to develop artificial intelligence (AI) voice-based smart devices that would make use of current technology to demonstrate how it can assist individuals with hearing difficulties. All of the items used in this project are commercially available especially, hearing components, microcontrollers, LCD module, Audio amplifier, wiring, and open-source code libraries.