A Dataset for recognition of Norwegian Sign Language

Authors

  • Benjamin Svendsen Department of Applied Data Science, Noroff University College, Kristiansand, Norway Author
  • Seifedine Kadry Department of Applied Data Science, Noroff University College, Kristiansand, Norway. https://orcid.org/0000-0002-1939-4842 Author

DOI:

https://doi.org/10.59543/ijmscs.v2i.8049

Keywords:

Dataset; Sign Language; Norwegian Sign Language

Abstract

Machine learning is a powerful tool in developing sign language recognition models, significantly enhancing communication accessibility for the deaf and hard-of-hearing community. However, such models' creation relies on the availability of comprehensive datasets, which are currently scarce for specific sign languages, particularly for Norwegian Sign Language (NSL). This paper introduces a unique dataset created to address this gap. The dataset, comprising 24,300 images of 27 NSL letters, was captured under varying conditions to represent each sign comprehensively. A man and a woman performed the signs. The goal of creating this dataset was to provide a robust foundation for further research in NSL recognition.

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Published

2023-08-05

How to Cite

Benjamin Svendsen, & Seifedine Kadry. (2023). A Dataset for recognition of Norwegian Sign Language. International Journal of Mathematics, Statistics, and Computer Science, 2, 1-3. https://doi.org/10.59543/ijmscs.v2i.8049

Issue

Vol. 2 (2024)

Section

Dataset

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

IJMSCS is published Open Access under a Creative Commons CC-BY 4.0 license. Authors retain full copyright, with the first publication right granted to the journal.