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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}, }
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