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Norwegian Sign Language: Overview of Resources and Experiments with Automatic SignWriting Transcription

Paper · 2026 · Elisabeth Othamar and Yves Scherrer

Summary

Norwegian Sign Language (NTS) has been officially recognised in Norway since 2022. Even so, researchers and developers still have almost no openly accessible, structured, annotated data for building sign recognition or translation systems. Othamar and Scherrer address this gap in two ways.

First, they survey existing and potential NTS data sources. They sort them by accessibility, format and usefulness for computational work, and they discuss the copyright, privacy and ethical obstacles to reusing them.

Second, they run pilot experiments on material never designed for machine learning: single-sign dictionary videos, SignWriting lexicons and NTS news broadcasts. These are processed with language-independent tools. The experiments test whether automatically generated SignWriting can serve as an intermediate representation and help identify signs within continuous signing. The authors present these experiments as preliminary, and the detailed results were not included in the text provided.

The paper matters as a documented starting point for building NTS resources. Its approach can also be transferred to other low-resource sign languages.

Key points

  • The Sign Language Dataset Compendium lists only lexical entries for NTS. Existing NTS datasets either have no annotation or are kept private, as is the case for the datasets described by Uddin et al. (2025) and by Svendsen and Kadry (2023).

  • The Norwegian Sign Language Corpus at NTNU groups four datasets collected between 2007 and 2024. Annotation is in progress, using multi-tier ELAN (EAF) files with glosses for each hand, non-manual markers and Norwegian/English translations.

  • Halvorsen (2012) contains 4 signers and 8 videos totalling 18 minutes. It is released under CC BY-NC-SA 4.0 but has no annotations or translations.

  • The other corpus datasets are:

    • Pilot Corpus (2015): 7 elderly deaf signers, 5.5 hours.
    • Depicting Perspective (2017–2018): 21 participants in 13 conversations, 7.5 hours.
    • Retellings and public events (2019–2024): 87 signers.

    Access to the first two requires an approved research plan, and redistribution is prohibited.

  • SignWriting and HamNoSys are presented as language-independent alternatives to glosses, which are specific to a given language and dataset. On that basis, SignWriting is tested as a pivot representation for NTS.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓University of OsloOslo · Norway51 works · 4,155 citations

 Fields, topics and concepts

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArtificial Intelligence · 16,194 worksArts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksPsychology · 1,552 worksDevelopmental and Educational Psychology · 499 worksHuman-Computer Interaction · 141 works

Cite

Cite as Elisabeth Othamar and Yves Scherrer. 2026. Norwegian Sign Language: Overview of Resources and Experiments with Automatic SignWriting Transcription. Proceedings of the LREC 2026 12th Workshop on the Representation and Processing of Sign Languages: Language in Motion.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.63317/3unezo3kea9w

@inproceedings{othamar2026norwegian,
  title = {{Norwegian Sign Language: Overview of Resources and Experiments with Automatic SignWriting Transcription}},
  author = {Elisabeth Othamar and Yves Scherrer},
  booktitle = {Proceedings of the LREC 2026 12th Workshop on the Representation and Processing of Sign Languages: Language in Motion},
  year = {2026},
  doi = {10.63317/3unezo3kea9w},
  url = {https://doi.org/10.63317/3unezo3kea9w}
}

References

23 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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