| --- |
| language: |
| - nb |
| - nn |
| - sv |
| - da |
| - 'no' |
| license: apache-2.0 |
| --- |
| ## SLIDE-fast |
|
|
| This is an updated version of the fast multilabel Scandinavian language identification model described in our [paper](https://aclanthology.org/2025.resourceful-1.33/). |
| The updated version is `able' to distinguish Nynorsk from Icelandic/Faroese, scoring Strict Accuracy **93.6** on our test dataset and **94.9** on [Haas and Derczynski, 2021](https://aclanthology.org/2021.vardial-1.8/). |
|
|
| ## Example usage |
|
|
| ```commandline |
| git clone git@github.com:ltgoslo/slide.git |
| cd src/ |
| python3 fast_usage_example.py |
| ``` |
|
|
| ## Cite us |
| ``` |
| @inproceedings{fedorova-etal-2025-multi, |
| title = "Multi-label {S}candinavian Language Identification ({SLIDE})", |
| author = "Fedorova, Mariia and |
| Frydenberg, Jonas Sebulon and |
| Handford, Victoria and |
| Lang{\o}, Victoria Ovedie Chruickshank and |
| Willoch, Solveig Helene and |
| Midtgaard, Marthe L{\o}ken and |
| Scherrer, Yves and |
| M{\ae}hlum, Petter and |
| Samuel, David", |
| editor = "Holdt, {\v{S}}pela Arhar and |
| Ilinykh, Nikolai and |
| Scalvini, Barbara and |
| Bruton, Micaella and |
| Debess, Iben Nyholm and |
| Tudor, Crina Madalina", |
| booktitle = "Proceedings of the Third Workshop on Resources and Representations for Under-Resourced Languages and Domains (RESOURCEFUL-2025)", |
| month = mar, |
| year = "2025", |
| address = "Tallinn, Estonia", |
| publisher = "University of Tartu Library, Estonia", |
| url = "https://aclanthology.org/2025.resourceful-1.33/", |
| pages = "179--189", |
| ISBN = "978-9908-53-121-2", |
| abstract = "Identifying closely related languages at sentence level is difficult, in particular because it is often impossible to assign a sentence to a single language. In this paper, we focus on multi-label sentence-level Scandinavian language identification (LID) for Danish, Norwegian Bokm{\r{a}}l, Norwegian Nynorsk, and Swedish. We present the Scandinavian Language Identification and Evaluation, SLIDE, a manually curated multi-label evaluation dataset and a suite of LID models with varying speed{--}accuracy tradeoffs. We demonstrate that the ability to identify multiple languages simultaneously is necessary for any accurate LID method, and present a novel approach to training such multi-label LID models." |
| } |
| ``` |
