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---
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 |