Instructions to use saattrupdan/wav2vec2-xls-r-300m-cv8-da with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saattrupdan/wav2vec2-xls-r-300m-cv8-da with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="saattrupdan/wav2vec2-xls-r-300m-cv8-da")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("saattrupdan/wav2vec2-xls-r-300m-cv8-da") model = AutoModelForCTC.from_pretrained("saattrupdan/wav2vec2-xls-r-300m-cv8-da") - Notebooks
- Google Colab
- Kaggle
XLS-R-300m-CV8-da
Model description
This model is a fine-tuned version of the multilingual acoustic model facebook/wav2vec2-xls-r-300m on the Danish part of Common Voice 8.0, containing ~6 crowdsourced hours of read-aloud Danish speech.
Performance
The model achieves the following WER scores (lower is better):
| Dataset | WER without LM | WER with 5-gram LM |
|---|---|---|
| Danish part of Common Voice 8.0 | 31.33 | 26.45 |
| Alvenir test set | 30.54 | 25.80 |
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Evaluation results
- wer on Danish Common Voice 8.0self-reported26.450
- wer on Alvenir ASR test datasetself-reported25.800