---
language:
- da
license: other
datasets:
- ftspeech
metrics:
- wer
tasks:
- automatic-speech-recognition
base_model: facebook/wav2vec2-xls-r-300m
model-index:
- name: wav2vec2-xls-r-300m-ftspeech
  results:
  - task:
      type: automatic-speech-recognition
    dataset:
      name: Danish Common Voice 8.0
      type: mozilla-foundation/common_voice_8_0
      args: da
    metrics:
    - type: wer
      value: 17.91
  - task:
      type: automatic-speech-recognition
    dataset:
      name: Alvenir ASR test dataset
      type: Alvenir/alvenir_asr_da_eval
    metrics:
    - type: wer
      value: 13.84
---

# XLS-R-300m-FTSpeech

## Model description

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the [FTSpeech dataset](https://ftspeech.github.io/), being a dataset of 1,800 hours of transcribed speeches from the Danish parliament.


## 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](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0/viewer/da/train) | 20.48 | 17.91 |
| [Alvenir test set](https://huggingface.co/datasets/Alvenir/alvenir_asr_da_eval) | 15.46 | 13.84 |


## License

The use of this model needs to adhere to [this license from the Danish Parliament](https://www.ft.dk/da/aktuelt/tv-fra-folketinget/deling-og-rettigheder).