README.md

---
language:
- it
license: apache-2.0
tags:
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
- it
- mozilla-foundation/common_voice_8_0
- speech
- wav2vec2
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
- cer
base_model: facebook/wav2vec2-xls-r-1b
model-index:
- name: XLS-R Wav2Vec2 Italian by radiogroup crits
  results:
  - task:
      type: automatic-speech-recognition
      name: Speech Recognition
    dataset:
      name: Common Voice 8.0 italian
      type: mozilla-foundation/common_voice_8_0
      args: it
    metrics:
    - type: wer
      value: 9.04
      name: Test WER
    - type: cer
      value: 2.2
      name: Test CER
    - type: wer
      value: 6.24
      name: Test WER (+LM)
    - type: cer
      value: 1.67
      name: Test CER (+LM)
---
# XLS-R-1B-ITALIAN-DOC4LM-5GRAM

## Fine-tuned XLS-R 1B model for speech recognition in Italian

Fine-tuned [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on Italian using the train and validation splits of [Common Voice 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0), [Multilingual TEDx](http://www.openslr.org/100), [Multilingual LibriSpeech](https://www.openslr.org/94/), and [Voxpopuli](https://github.com/facebookresearch/voxpopuli).

When using this model, make sure that your speech input is sampled at 16kHz.


## Language model information

Our language model was generated using a dataset of Italian wikipedia articles and manual transcriptions of radio newspapers and television programs. 


## Download CommonVoice8.0 dataset for italian language
```python
from datasets import load_dataset

dataset = load_dataset("mozilla-foundation/common_voice_8_0", "it", use_auth_token=True)
```

## Evaluation Commands

To evaluate on `mozilla-foundation/common_voice_8_0` with split `test`:

```bash
python eval.py --model_id radiogroup-crits/wav2vec2-xls-r-1b-italian-doc4lm-5gram --dataset mozilla-foundation/common_voice_8_0 --config it --split test --log_outputs --greedy

mv log_mozilla-foundation_common_voice_8_0_it_test_predictions.txt log_mozilla-foundation_common_voice_8_0_it_test_predictions_greedy.txt

mv log_mozilla-foundation_common_voice_8_0_it_test_targets.txt log_mozilla-foundation_common_voice_8_0_it_test_targets_greedy.txt

mv mozilla-foundation_common_voice_8_0_it_test_eval_results.txt mozilla-foundation_common_voice_8_0_it_test_eval_results_greedy.txt

python eval.py --model_id radiogroup-crits/wav2vec2-xls-r-1b-italian-doc4lm-5gram --dataset mozilla-foundation/common_voice_8_0 --config it --split test --log_outputs

mv log_mozilla-foundation_common_voice_8_0_it_test_predictions.txt log_mozilla-foundation_common_voice_8_0_it_test_predictions_lm.txt

mv log_mozilla-foundation_common_voice_8_0_it_test_targets.txt log_mozilla-foundation_common_voice_8_0_it_test_targets_lm.txt

mv mozilla-foundation_common_voice_8_0_it_test_eval_results.txt mozilla-foundation_common_voice_8_0_it_test_eval_results_lm.txt
```

## Citation
If you want to cite this model you can use this:

```bibtex
@misc{crits2022wav2vec2-xls-r-1b-italian-doc4lm-5gram,
  title={XLS-R Wav2Vec2 Italian by radiogroup crits},
  author={Teraoni Prioletti Raffaele, Casagranda Paolo and Russo Francesco},
  publisher={Hugging Face},
  journal={Hugging Face Hub},
  howpublished={\url{https://huggingface.co/radiogroup-crits/wav2vec2-xls-r-1b-italian-doc4lm-5gram}},
  year={2022}
}
```