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license: apache-2.0 |
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--- |
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## Citation |
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```bibtex |
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@inproceedings{de-la-rosa-etal-2023-boosting, |
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title = "Boosting {N}orwegian Automatic Speech Recognition", |
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author = "De La Rosa, Javier and |
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Braaten, Rolv-Arild and |
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Kummervold, Per and |
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Wetjen, Freddy", |
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booktitle = "Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)", |
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month = may, |
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year = "2023", |
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address = "T{\'o}rshavn, Faroe Islands", |
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publisher = "University of Tartu Library", |
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url = "https://aclanthology.org/2023.nodalida-1.55", |
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pages = "555--564", |
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abstract = "In this paper, we present several baselines for automatic speech recognition (ASR) models for the two official written languages in Norway: Bokm{\aa}l and Nynorsk. We compare the performance of models of varying sizes and pre-training approaches on multiple Norwegian speech datasets. Additionally, we measure the performance of these models against previous state-of-the-art ASR models, as well as on out-of-domain datasets. We improve the state of the art on the Norwegian Parliamentary Speech Corpus (NPSC) from a word error rate (WER) of 17.10{\%} to 7.60{\%}, with models achieving 5.81{\%} for Bokm{\aa}l and 11.54{\%} for Nynorsk. We also discuss the challenges and potential solutions for further improving ASR models for Norwegian.", |
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} |
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``` |