Language diversity presents a significant challenge in effective communication, particularly in multi- lingual regions such as India. While existing translation systems provide partial solutions, most operate in isolation—handling text, speech, or visual data independently resulting in fragmented interactions and loss of contextual meaning. Vernafy is proposed as an AI-powered multimodal Natural Language Processing (NLP) platform designed to enable seamless, context aware translation and interaction across multiple modalities, including text, speech, and images. The system integrates advanced NLP techniques with speech recognition, text-to-speech synthesis, optical character recognition, and summarization to deliver accurate and natural communication in real time. By unifying these capabilities into a single, user-friendly interface, Vernafy enhances accessibility for educators, businesses, con- tent creators, and users with linguistic or sensory limitations. Special emphasis is placed on preserving tone, intent, and cultural nuances to ensure meaningful interactions rather than mechanical translations. Additionally, Vernafy supports linguistic inclusivity by enabling regional and lesser-known languages to coexist with globally dominant languages, thereby contributing to cultural preservation and digital equality. The proposed system demonstrates how multimodal AI can be effectively leveraged to overcome language barriers, improve cross-lingual communication, and create an inclusive digital ecosystem.
Gupta et al. (Thu,) studied this question.