ABSTRACT
Communication barriers between the hearing impaired and non-signers often lead to misunderstandings and difficulties in daily interactions. Indian Sign Language (ISL) serves as a vital means of communication for the deaf community in India, yet its comprehension is limited among non-signers. This paper proposes a novel approach for ISL recognition and translation to speech, aiming to bridge the communication gap between the hearing impaired and non-signers. Our system employs computer vision techniques for hand gesture recognition, followed by translation into spoken language using text-to-speech synthesis. Through the integration of advanced machine learning algorithms and linguistic processing, our system enables real-time interpretation of ISL gestures, facilitating seamless communication between individuals with hearing impairments and those unfamiliar with sign language.
