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Author(s):

R.Sowmiya | M.Saniya | B.Shafeek Ahamed | J.Nikile Eines Dhoni | S.Mohamed Shath
Keywords:

AI, Sign Language Recognition, ISL, Trans Former, Real-Time System, Gesture Recognition, TTS, Speech Recognition.
Abstract:
Deaf And Mutes Use Sign Language To Communicate, Yet Communication Between Signers And Non-signers Is Challenging As There Is A Lack Of Awareness. This Lays Obstacles In Such Spheres As Education, Medical Care, And Government Services. The Current Systems Have Shortcomings Such As Limited Vocabulary, Inadequate Real Time Operation, Support Of The Indian Sign Language And No. Effective Two-way Communication. This Project Sug Gests An AI-based Communication To Deal With These Challenges. System That Facilitates A Smooth Interaction Between Sign-language And Nonsigners. The Model Is Based On Transformer To Identify Continuous. Facial Expressions, Body Movements, And Gestures Of Live Video Input, Providing Proper And Real-time Interpretation Of The Sign Language. It Also Incorporates Speech Recognition And Text To Speech Modules In Order To Translate. Translates Voice Text And Voice Even In A Noisy Setting. Another Component Of A Neural Avatar Is A Neural Sign Animation To. Visually Represent Communication. The System Is Adopted As Web-based Application, Which Is Accessible. And Ease Of Use. Overall, The Proposed System Enhances Inclusive Communication And Breaks The Barrier Between Deaf And The Hearing Communities.