Integration of ASL and FSL Recognition with YOLOv7

American Sign Language (ASL) and Filipino Sign Language (FSL) vary in grammar and vocabulary, posing communication barriers for Deaf and hard-of-hearing people. Although sign language-to-speech technology can help to bridge this gap, there are still obstacles, such as effectively interpreting hand forms, gestures, and facial emotions. Developing reliable programs requires large datasets, which might be challenging for FSL due to regional differences. Sensor technologies, computer vision, and machine learning innovations solve the problems. YOLOv7's real-time object detection capabilities capture complex hand movements and gestures. The study demonstrates the potential of YOLOv7 in enhancing sign language recognition for improved communication between Deaf and hearing individuals.