[35] Prem Selvaraj, Gokul Nc, Pratyush Kumar, and Mitesh Khapra. OpenHands: Making sign language recognition accessible with pose-based pretrained models across languages. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2114-2133, Dublin, Ireland, May 2022. Association for Computational Linguistics. doi: 10.18653/v1/2022.acl-long.150. URL https://aclanthology.org/2022.acl-long.150.
[36] Noam Shazeer and Mitchell Stern. Adafactor: Adaptive learning rates with sublinear memory cost. In Jennifer Dy and Andreas Krause, editors, Proceedings of the 35th International Conference on Machine Learning, volume 80 of Proceedings of Machine Learning Research, pages 4596-4604. PMLR, 10-15 Jul 2018. URL https://proceedings.mlr.press/v80/shazeer18a.html.
[37] Bowen Shi, Aurora Martinez Del Rio, Jonathan Keane, Jonathan Michaux, Diane Brentari, Greg Shakhnarovich, and Karen Livescu. American Sign Language fingerspelling recognition in the wild. In 2018 IEEE Spoken Language Technology Workshop (SLT), pages 145-152, 2018. URL https://doi.org/10.1109/SLT.2018.8639639.
[38] Bowen Shi, Aurora Martinez Del Rio, Jonathan Keane, Diane Brentari, Greg Shakhnarovich, and Karen Livescu. Fingerspelling recognition in the wild with iterative visual attention. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), October 2019. URL https://doi.org/10.1109/ICCV.2019.00550.
[39] Bowen Shi, Diane Brentari, Greg Shakhnarovich, and Karen Livescu. Open-domain sign language translation learned from online video, 2022. URL https://arxiv.org/abs/2205.12870.
[40] Laia Tarres, Gerard I. Gállego, Amanda Duarte, Jordi Torres, and Xavier Giro i Nieto. Sign language translation from instructional videos, 2023. URL https://arxiv.org/abs/2304.06371.
[41] Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. Attention is all you need. In I. Guyon, U. Von Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, editors, Advances in Neural Information Processing Systems, volume 30. Curran Associates, Inc., 2017. URL https://proceedings.neurips.cc/paper_files/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf.
[42] Aoxiong Yin, Zhou Zhao, Weike Jin, Meng Zhang, Xingshan Zeng, and Xiaofei He. MLSLT: Towards multilingual sign language translation. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 5099-5109, 2022. URL https://doi.org/10.1109/CVPR52688.2022.00505.
[43] Kayo Yin and Jesse Read. Better sign language translation with STMC-transformer. In Proceedings of the 28th International Conference on Computational Linguistics, pages 5975-5989, Barcelona, Spain (Online), December 2020. International Committee on Computational Linguistics. doi: 10.18653/v1/2020.coling-main.525. URL https://aclanthology.org/2020.coling-main.525.
[44] Kayo Yin, Amit Moryossef, Julie Hochgesang, Yoav Goldberg, and Malihe Alikhani. Including signed languages in natural language processing, 2021. URL https://arxiv.org/abs/2105.05222.
[45] Biao Zhang, Mathias Müller, and Rico Sennrich. SLTUNET: A simple unified model for sign language translation. In The Eleventh International Conference on Learning Representations, 2023. URL https://openreview.net/forum?id=EBS4C77p_5S.
[46] Hao Zhou, Wengang Zhou, Yun Zhou, and Houqiang Li. Spatial-temporal multi-cue network for continuous sign language recognition. Proceedings of the AAAI Conference on Artificial Intelligence, 34(07):13009-13016, Apr. 2020. doi: 10.1609/aaai.v34i07.7001. URL https://ojs.aaaai.org/index.php/AAAI/article/view/7001.