Deep learning based sign language recognition and translation with an integrated reply bot

Abstract

Effective communication is a universal need; however, individuals who rely on sign language often encounter barriers when interacting with non-signers. This paper presents a system that employs deep learning techniques to recognize sign language gestures and translate them into text and speech in real time. By combining image capture, preprocessing, and an interactive reply bot, the system not only bridges the communication gap but also provides immediate user feedback in simple, everyday language. We detail the system’s design, methodology, experimental setup, results, and areas for future enhancement.