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@article{180974,
        author = {B.Ritheesh Reddy and CH.Gayathri and T.Nikitha and V.Charan teja and J.Naresh Kumar},
        title = {SIGNBRIDGE – Audio to Sign Language Translator Using NLP},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {3464-3469},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180974},
        abstract = {This project introduces an innovative 
approach to bridging the communication gap between the 
hearing and speech-impaired communities through real
time sign language translation. SIGNBRIDGE harnesses 
the power of Natural Language Processing (NLP) to 
convert spoken audio into accurate sign language 
representations. By analyzing speech input, the system 
processes linguistic content, removes ambiguity, and 
maps it to corresponding sign gestures. Through 
advanced language modeling and gesture mapping 
algorithms, SIGNBRIDGE enables effective two-way 
communication, making public services, education, and 
emergency responses more inclusive. This project has the 
potential to transform assistive technology, enhancing 
accessibility and empowering millions with seamless 
interaction in diverse environments.},
        keywords = {Natural Language Processing (NLP),  Speech Recognition, Sign Language Translation,  Assistive Technology, Audio Processing, Gesture  Mapping,  Human-Computer Interaction (HCI),  Accessibility.},
        month = {June},
        }