A SURVEY ON RECOGNIZING SIGN LANGUAGE USING DEEP LEARNING

Effective communication hinges on the exchange of information, ideas, and emotions, necessitating a shared language. For individuals with speech impairments, sign language serves as a vital means of communication, but a lack of understanding can pose significant challenges when interacting with those without impairments. To address this, a machine learning-based model can be developed to recognize various sign language motions and convert them into a universal language, facilitating interactions with speech-impaired individuals. While existing Sign Language Recognition systems have limitations in recognizing multiple languages, this article introduces a real-time Sign Language Recognition system that employs transfer learning with TensorFlow and utilizes a webcam to detect and interpret sign language gesture.