Paper Key : IRJ************440
Author: Tanishka Kailas Aher,Kashish Ramesh Ugale,Diksha Sunil Gaikwad,Vaishnavi Balu Ugale,Prof. K.v Karad
Date Published: 03 Apr 2025
Abstract
The proposed solution is a cutting-edge real-time Sign Language to text and speech translation application designed to bridge communication gaps between the deaf and hard-of-hearing community. This application aims to enhance accessibility and inclusivity by converting sign language gestures into accurate, readable text and natural-sounding speech in multiple Indian languages, including Hindi, Marathi. Utilizing advanced computer vision and machine learning technologies, the application will recognize and interpret a comprehensive library of signs and gestures with high precision. Through the integration of convolutional neural networks (CNNs) and natural language processing (NLP), the system will deliver real-time translation, ensuring that users receive immediate and contextually relevant text and speech outputs. The application will feature an intuitive, user-friendly interface that simplifies interaction, making it accessible for both SL users and hearing individuals. Additionally, adaptive learning mechanisms will continuously improve the system's accuracy based on user feedback and interactions. This innovative solution is designed to significantly empower individuals who rely on SL, fostering greater understanding and engagement in various aspects of daily life and promoting a more inclusive society.
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