This paper presents a semi-automatic annotation tool for sign languages namely SLAN-tool. The SLAN-tool provides a web-based service for the annotation of sign language videos. Researchers can use the SLAN-tool web service to annotate new and existing sign language datasets with different types of annotations, such as gloss, handshape configurations, and signing regions. This is allowed using a custom tier adding functionality. A unique feature of the tool is its automatic annotation functionality which uses several neural network models in order to recognize signing segments from videos and classify handshapes according to HamNoSys handshape inventory. Furthermore, SLAN-tool users can export annotations and import them into ELAN. The SLAN-tool is publicly available at https://slan-tool.com.
@inproceedings{mukushev:22030:sign-lang:lrec,
author = {Mukushev, Medet and Sabyrov, Arman and Sultanova, Madina and Kimmelman, Vadim and Sandygulova, Anara},
title = {Towards Semi-automatic Sign Language Annotation Tool: {SLAN-tool}},
pages = {159--164},
editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna and Schulder, Marc},
booktitle = {Proceedings of the {LREC2022} 10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources},
maintitle = {13th International Conference on Language Resources and Evaluation ({LREC} 2022)},
publisher = {{European Language Resources Association (ELRA)}},
address = {Marseille, France},
day = {25},
month = jun,
year = {2022},
isbn = {979-10-95546-86-3},
language = {english},
url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/22030.pdf}
}