A two-stage deep learning model classifies Indian sign language video clips into English words using a fine-tuned VideoMAE transformer, achieving 99% training and 78% validation accuracy on a 13-class dataset. The predicted English labels are translated into Hindi, Telugu, and Bengali using Meta AI's NLLB-200 multilingual model, with a Streamlit demo enabling user-uploaded video inference and cross-lingual output.
Deep Learning Pipeline for Sign Language Recognition and Translation to Indian Vernaculars
from English