Bangla Sign Language

Bangla Sign Language (BdSL) research focuses on developing automated systems for recognizing and interpreting BdSL, aiming to bridge communication gaps for the deaf community. Current research employs deep learning models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs like LSTMs and GRUs), and Graph Neural Networks (GNNs), often incorporating techniques like transfer learning and attention mechanisms, to achieve high accuracy in recognizing both isolated signs and continuous sign language. The creation and sharing of large, well-annotated BdSL datasets, encompassing both static images and dynamic videos at the character, word, and even sentence levels, are crucial for advancing this field and enabling the development of practical applications like real-time translation systems and assistive technologies. This work is significant because it addresses the underrepresentation of low-resource sign languages in the broader field of sign language recognition.