README.md

---
license: cc-by-nc-sa-4.0
language:
- fr
metrics:
- wer
library_name: speechbrain
pipeline_tag: automatic-speech-recognition
tags:
- CTC
- pytorch
- asr
- speechbrain
- spontaneous speech
---

### Wav2Vec 2.0 with CTC trained on spontaneous speech data
- who developed the system
- model date: Jan 2024
- model version: 1.0
- model type: automatic speech recognition system
- Info about training algo, parameters, fairness constraints or other applied approaches, and features
```
@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}},
  }
```
- citation details
```
@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}},
  }
```
- license
- contact
Solène Evain ([email protected])

### Intended Use
- primary intended use
- primary intended users
- out-of-scope use cases

### Factors

### Metrics
| Release | Test CER | GPUs |
|:-------------:|:--------------:|:--------:|
| 22-02-23 | 4.78 | 1xV100 32GB |

### Evaluation data
- datasets
- motivation
- preprocessing

### Training data

### Quantitative analyses

### Ethical considerations

### Caveats and recommendations
We do not provide any warranty on the performance achieved by this model when used on other datasets

#### About SpeechBrain
SpeechBrain is an open-source and all-in-one speech toolkit. It is designed to be simple, extremely flexible, and user-friendly. Competitive or state-of-the-art performance is obtained in various domains.

Website: https://speechbrain.github.io/

GitHub: https://github.com/speechbrain/speechbrain