In the past decade, sign language research has achieved remarkable results alongside the advancements in deep learning. However, there is a disconnect between the outcomes of these research efforts and the actual use of sign language by signers. In this position paper, we reviewed sign language papers related to deep learning published in the last ten years to explore reasons for this gap. We found many areas of research that are still underdeveloped, despite their linguistic importance. Based on an analysis of known corpora and methodologies, we identified the reasons for the lack of progress in these areas and propose directions for future research efforts.
@inproceedings{kim:24028:sign-lang:lrec,
author = {Kim, Jung-Ho and Ko, Changyong and Huerta-Enochian, Mathew and Ko, Seung Yong},
title = {Shedding Light on the Underexplored: Tackling the Minor Sign Language Research Topics},
pages = {240--251},
editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Mesch, Johanna and Schulder, Marc},
booktitle = {Proceedings of the {LREC-COLING} 2024 11th Workshop on the Representation and Processing of Sign Languages: Evaluation of Sign Language Resources},
maintitle = {2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation ({LREC-COLING} 2024)},
publisher = {{ELRA Language Resources Association (ELRA) and the International Committee on Computational Linguistics (ICCL)}},
address = {Torino, Italy},
day = {25},
month = may,
year = {2024},
isbn = {978-2-493814-30-2},
language = {english},
url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/24028.pdf}
}