Indian Sign Language to Text/Speech Translation: A Deep Learning

Abstract

This research paper presents a novel approach to translating Indian Sign Language (ISL) gestures into text and speech using deep learning techniques. With the growing need for inclusive communication technologies, our system aims to bridge the gap between the deaf and hearing communities. We explore the implementation of computer vision and natural language processing (NLP) techniques to recognize and interpret ISL signs, providing real-time text and speech output. Our study evaluates model performance, challenges faced, and potential future improvements to enhance accuracy and usability. This work contributes to the field of assistive technology and sign language processing by providing a scalable and efficient model for ISL recognition.