For publishing sign language corpus data on the web, anonymization is crucial even if it is impossible to hide the visual appearance of the signers: In a small community, even vague references to third persons may be enough to identify those persons. In the case of the DGS Korpus (German Sign Language corpus) project, we want to publish data as a contribution to the cultural heritage of the sign language community while annotation of the data is still ongoing. This poses the question how well anonymization can be achieved given that no full linguistic analysis of the data is available. Basically, we combine analysis of all data that we have, including named entity recognition on translations into German. For this, we use the WebLicht language technology infrastructure. We report on the reliability of these methods in this special context and also illustrate how the anonymization of the video data is technically achieved in order to minimally disturb the viewer.
@inproceedings{bleicken-etal-2016-using:lrec,
author = {Bleicken, Julian and Hanke, Thomas and Salden, Uta and Wagner, Sven},
title = {Using a Language Technology Infrastructure for {G}erman in order to Anonymize {G}erman {S}ign {L}anguage Corpus Data},
pages = {3303--3306},
editor = {Calzolari, Nicoletta and Choukri, Khalid and Declerck, Thierry and Goggi, Sara and Grobelnik, Marko and Maegaard, Bente and Mariani, Joseph and Mazo, H{\'e}l{\`e}ne and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios},
booktitle = {10th International Conference on Language Resources and Evaluation ({LREC} 2016)},
publisher = {{European Language Resources Association (ELRA)}},
address = {Portoro{\v z}, Slovenia},
day = {23--28},
month = may,
year = {2016},
isbn = {978-2-9517408-9-1},
language = {english},
url = {https://aclanthology.org/L16-1526}
}
| Salden, Uta | Wagner, Sven