---
language: "fr"
thumbnail:
tags:
- ASR
- CTC
- Attention
- pytorch
- speechbrain
- Transformer
license: "apache-2.0"
datasets:
- commonvoice
metrics:
- wer
- cer
---

# wav2vec 2.0 with CTC/Attention trained on CommonVoice French (No LM)

This repository provides all the necessary tools to perform automatic speech
recognition from an end-to-end system pretrained on CommonVoice (French Language) within
SpeechBrain. For a better experience, we encourage you to learn more about
[SpeechBrain](https://speechbrain.github.io). The given ASR model performance are:

| Release | Test CER | Test WER | GPUs |
|:-------------:|:--------------:|:--------------:| :--------:|
| 29-04-21 | 9.62 | 13.90 | 2xV100 32GB |

## Pipeline description

This ASR system is composed of 2 different but linked blocks:
1. Tokenizer (unigram) that transforms words into subword units and trained with
the train transcriptions (train.tsv) of CommonVoice (FR).
3. Acoustic model (wav2vec2.0 + CTC/Attention). A pretrained wav2vec 2.0 model ([wav2vec2-large-xlsr-53-french](https://huggingface.co/facebook/wav2vec2-large-xlsr-53-french)) is combined with two DNN layers and finetuned on CommonVoice FR. 
The obtained final acoustic representation is given to the CTC and attention decoders.

## Intended uses & limitations

This model has been primarily developed to be run within SpeechBrain as a pretrained ASR model
for the French language. Thanks to the flexibility of SpeechBrain, any of the 2 blocks
detailed above can be extracted and connected to your custom pipeline as long as SpeechBrain is
installed.

## Install SpeechBrain

First of all, please install tranformers and SpeechBrain with the following command:

```
pip install speechbrain transformers
```

Please notice that we encourage you to read our tutorials and learn more about
[SpeechBrain](https://speechbrain.github.io).

### Transcribing your own audio files (in French)

```python
from speechbrain.pretrained import EncoderDecoderASR

asr_model = EncoderDecoderASR.from_hparams(source="speechbrain/asr-crdnn-commonvoice-fr", savedir="pretrained_models/asr-crdnn-commonvoice-fr")
asr_model.transcribe_file("example-fr.wav")

```

#### Referencing SpeechBrain

```
@misc{SB2021,
    author = {Ravanelli, Mirco and Parcollet, Titouan and Rouhe, Aku and Plantinga, Peter and Rastorgueva, Elena and Lugosch, Loren and Dawalatabad, Nauman and Ju-Chieh, Chou and Heba, Abdel and Grondin, Francois and Aris, William and Liao, Chien-Feng and Cornell, Samuele and Yeh, Sung-Lin and Na, Hwidong and Gao, Yan and Fu, Szu-Wei and Subakan, Cem and De Mori, Renato and Bengio, Yoshua },
    title = {SpeechBrain},
    year = {2021},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {\\\\url{https://github.com/speechbrain/speechbrain}},
  }
```