Sign Language Datasets for French Belgian Sign Language

This dataset is built upon the work of Belgian linguists from the University of Namur. During eight years, they've collected and annotated 50 hours of videos depicting sign language conversation. 100 signers were recorded, making it one of the most representative sign language corpus. The annotation has been sanitized and enriched with metadata to construct two, easy to use, datasets for sign language recognition. One for continuous sign language recognition and the other for isolated sign recognition.

LSFB-CONT

The dataset for continuous sign language recognition is made of over 25h of video clips. Each clip is associated with a time-aligned annotation file containing the start and the end of each sign along with a gloss (label) associated with all unique signs. Mediapipe pose and hands information were also computed for each video clip and these metadata are made available in the dataset.

LSFB-ISOL

The isolated version of the dataset contains only clips showing one isolated sign issued from the LSFB-CONT dataset. We chose to keep all the signs with at least 40 examples, leading to a dataset containing over 50 000 clips for 635 different glosses (labels). The Mediapipe metadata is also available for this dataset.