GSLW: The dataset has been recorded under various background and lighting variations and with different smartphones. The camera position and orientation are gently varied among subsequent recordings to increase video diversity. 15 cases of hearing-impaired people dealing with public services have been recorded. The resulting test dataset has 1,736 videos that were annotated both at individual gloss and sentence level. Instructions: GSLW.csv file has the paths, gloss and sentence annotations of the videos. load_gslw.py has a python function to load the GSLW.csv file for training or inference. Citation: If you use our dataset please cite our work : @article{gsl, author={N. M. {Adaloglou} and T. {Chatzis} and I. {Papastratis} and A. {Stergioulas} and G. T. {Papadopoulos} and V. {Zacharopoulou} and G. {Xydopoulos} and K. {Antzakas} and D. {Papazachariou} and P. n. {Daras}}, journal={IEEE Transactions on Multimedia}, title={A Comprehensive Study on Deep Learning-based Methods for Sign Language Recognition}, year={2021}, volume={}, number={}, pages={1-1}, doi={10.1109/TMM.2021.3070438}}

Acknowledgments This work was supported by the Greek General Secretariat of Research and Technology under contract Τ1ΕΔΚ-02469 EPIKOINONO.