American Sign Language Real Time Detection Using TensorFlow and Keras in Python

This paper presents a novel approach to enhance communication for individuals with hearing impairments. We propose a sign language detection program in Python that integrates image recognition techniques to synthesize American Sign Language (ASL). The program achieves accurate recognition by analysing and interpreting ASL gestures using a convolutional neural network. The detected gestures are mapped to textual representations and relayed to the display interface for seamless communication. Evaluation of a diverse data set demonstrates the system's robustness and effectiveness. The developed program, implemented in Python using OpenCV and TensorFlow, offers a scalable solution to improve accessibility and inclusivity for the hearing-impaired community.