Computational Annotation for Sign Language Data

This PhD research focuses on developing automatic methods for annotating sign language data, which is crucial for advancing Sign Language Machine Translation (SLMT). This project explores an emerging topic informed by ongoing research in Artificial Intelligence (AI) and SLMT. Key areas include:

- Sign language recognition

- Video key point extraction

- Annotation techniques for documenting sign language, which is visual and gestural with no written form

- Sign language linguistics and computational linguistics

The main objective is to create a method for recognizing and encoding sign language data into a suitable annotation format that can be further processed computationally.