Fostering Inclusive Communication: A Tool Integrating Machine Translation, NLP, and Audio-to-Sign-Language Conversion for the Deaf

Approximately 70 million individuals worldwide grapple with deafness or muteness, presenting challenges in communication. This article presents a novel solution: an audio-to-sign-language converter. Sign language, a visual medium for speech, is pivotal in bridging this communication gap. This Python-based converter interprets user input, transforming it into gestures, facilitating interaction between the hearing and the deaf. It also serves as a valuable tool for learning sign language. Live voice input, captured through a microphone, undergoes advanced Natural Language Processing techniques to be converted into text. Recognized phrases trigger relevant gesture videos or display corresponding letters. The application also features a termination command, "goodbye." With potential applications in web and mobile platforms, two-way interaction, and video integration, this converter holds promise in enhancing accessibility for the deaf community, fostering inclusivity and effective communication. This paper is a significant step towards facilitating meaningful connections between individuals with disabilities and their non-disabled peers.