[11] Mathieu De Coster, Karel D'Oosterlinck, Marija Pizurica, Paloma Rabaey, Severine Verlinden, Mieke Van Herreweghe, and Joni Dambre. Frozen pretrained transformers for neural sign language translation. In Proceedings of the 1st International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL), pages 88-97, Virtual, August 2021. Association for Machine Translation in the Americas. URL https://aclanthology.org/2021.mtsummit-at4ssl.10.
[12] Mathieu De Coster, Dimitar Shterionov, Mieke Van Herreweghe, and Joni Dambre. Machine translation from signed to spoken languages: State of the art and challenges. Universal Access in the Information Society, pages 1-27, 2023. URL https://doi.org/10.1007/s10209-023-00992-1.
[13] Amanda Duarte, Shruti Palaskar, Lucas Ventura, Deepti Ghadiyaram, Kenneth DeHaan, Florian Metze, Jordi Torres, and Xavier Giro-i Nieto. How2Sign: A large-scale multimodal dataset for continuous American Sign Language. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 2735-2744, June 2021. URL https://doi.org/10.1109/CVPR46437.2021.00276.
[14] Google-Research. Google-research/bleurt: Bleurt is a metric for natural language generation based on transfer learning. URL https://github.com/google-research/bleurt.
[15] Naman Goyal, Cynthia Gao, Vishrav Chaudhary, Peng-Jen Chen, Guillaume Wenzek, Da Ju, Sanjana Krishnan, Marc'Aurelio Ranzato, Francisco Guzman, and Angela Fan. The flores-101 evaluation benchmark for low-resource and multilingual machine translation, 2021.
[16] Ivan Grishchenko and Valentin Bazarevsky. Mediapipe holistic - simultaneous face, hand and pose prediction, on device, Dec 2020. URL https://ai.googleblog.com/2020/12/mediapipe-holistic-simultaneous-face.html.
[17] Shester Gueuwou, Kate Takyi, Mathias Müller, Marco Stanley Nyarko, Richard Adade, and Rose-Mary Owusuaa Mensah Gyening. Afrisign: Machine translation for african sign languages. In 4th Workshop on African Natural Language Processing, 2023. URL https://openreview.net/forum?id=EHldk3J2xk.
[18] Thomas Hanke, Marc Schulder, Reiner Konrad, and Elena Jahn. Extending the Public DGS Corpus in size and depth. In Proceedings of the LREC2020 9th Workshop on the Representation and Processing of Sign Languages: Sign Language Resources in the Service of the Language Community, Technological Challenges and Application Perspectives, pages 75-82, Marseille, France, May 2020. European Language Resources Association (ELRA). ISBN 979-10-95546-54-2. URL https://aclanthology.org/2020/signlang-1.12.
[19] Abhinav Joshi, Ashwani Bhat, Pradeep S, Priya Gole, Shashwat Gupta, Shreyansh Agarwal, and Ashutosh Modi. CISLR: Corpus for Indian Sign Language recognition. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 10357-10366, Abu Dhabi, United Arab Emirates, December 2022. Association for Computational Linguistics. doi: 10.18653/v1/2022.emnlp-main.707. URL https://aclanthology.org/2022.emnlp-main.707.
[20] Pratik Joshi, Sebastin Santy, Amar Budhiraja, Kalika Bali, and Monjit Choudhury. The state and fate of linguistic diversity and inclusion in the nlp world, 2021. URL https://arxiv.org/abs/2004.09095.
[21] Hamid Reza Vaezi Joze and Oscar Koller. MS-ASL: A large-scale data set and benchmark for understanding american sign language. CoRR, abs/1812.01053, 2018. URL http://arxiv.org/abs/1812.01053.
[22] Sang-Ki Ko, Chang Jo Kim, Hyedong Jung, and Choongsang Cho. Neural sign language translation based on human keypoint estimation. Applied Sciences, 9(13), 2019. ISSN 2076-3417. doi: 10.3390/app9132683. URL https://www.mdpi.com/2076-3417/9/13/2683.
[23] Taku Kudo and John Richardson. SentencePiece: A simple and language independent subword tokenizer and detokenizer for neural text processing. In Proceedings of the 2018 Conference