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Real-Time AI-Powered Sign Language Translation System for Inclusive Communication

Year: 2025

Type: article

Abstract: In order to address communication barriers between hearing and deaf people, this paper describes the creation of an AI- based application that enables real-time translation of sign language into speech and text. Convolutional Neural Networks (CNNs), Media Pipe for real-time gesture recognition, an easy-to-use user interface, and a feedback loop for ongoing enhancement are all features of the system. The suggested system improves accessibility and inclusivity in fields like public services, healthcare, and education. Future developments will include support for more sign languages and integration with wearable technology.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.16079560

Authors: Sadiya Mehreen, Saima Mahveen, Amritdeep Kaur, Sneha Jadhav, Prof. Ashwini Biradar

Language: English

Topic: Hand Gesture Recognition Systems

Subfield: Human-Computer Interaction

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6893456833

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