Continuous Sign Language Recognition Using MediaPipe

According to WHO, more than 5% of the world’s population suffer from hearing loss. They estimate that by 2050, the figure will reach over 700 million people. Therefore, the need for a sign language translation technique is essential. However, that has not been an effective approach to recognize dynamic sign language in real-time. This paper proposed the new method to continuous translate sign language recognition in real-time using Convolutional Neural Network and Long-Short term Memory. With the help of extracting coordinates of body joints from MediaPipe, it reaches an overall accuracy up to 99.5%.