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| Français de | Corpus | Heures |
|---|---|---|
| France | TCOF | 23h |
| France | ESLO2 | 41h22 |
| France | CLAPI | 2h05 |
| France | CFPP | 35h47 |
| France | C-ORAL-ROM | 16h05 |
| France | REUNIONS | 9h36 |
| France | CID | 6h32 |
| France | TUFS | 27h15 |
| France | CRFP | 25h57 |
| France | PFC | 13h14 |
| France | FLEURON | 2h18 |
| N/A | PFC | 10h12 |
| N/A | TCOF | 2h33 |
| N/A | MPF | 17h50 |
| Suisse | OFROM | 18h16 |
| Suisse | PFC | 5h13 |
| Belgique | CFPB | 7h39 |
| Système | Usual_close | Unusual_close | Unusual_distant | AllCases | AllSpont | ETAPE | CV 6.1 |
|---|---|---|---|---|---|---|---|
| Whisper large-v2 | 51.97 | 23.36 | 13.44 | 29.41 | 26.80 | 27.81 | 21.69 |
| asr-wav2vec2-commonvoice-fr (CV 6.1, LeBenchmark-7k-large) | 80.85 | 52.66 | 32.16 | 55.14 | 51.2 | 36.55 | 9.97 |
pip install speechbrain transformers1from speechbrain.inference.ASR import EncoderASR
2
3asr_model = EncoderASR.from_hparams(source="Sevain/asr-wav2vec2-LB7K-spontaneous-fr", savedir="pretrained_models/asr-wav2vec2-LB7K-spontaneous-fr")
4asr_model.transcribe_file('path/to/your/file')@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 = {https://github.com/speechbrain/speechbrain},
}
@phdthesis{evain:tel-04984659,
TITLE = {{Dimensions de variation de la parole spontan{\'e}e pour l'{\'e}tude inter-corpus des performances de syst{\`e}mes de reconnaissance automatique de la parole}},
AUTHOR = {Evain, Sol{\`e}ne},
URL = {https://theses.hal.science/tel-04984659},
NUMBER = {2024GRALM037},
SCHOOL = {{Universit{\'e} Grenoble Alpes}},
YEAR = {2024},
MONTH = Oct,
KEYWORDS = {Automatic speech recognition ; Spontaneous speech ; Deep learning ; Reconnaissance automatique de la parole ; Parole spontan{\'e}e ; Apprentissage profond},
TYPE = {Theses},
PDF = {https://theses.hal.science/tel-04984659v1/file/EVAIN_2024_archivage.pdf},
HAL_ID = {tel-04984659},
HAL_VERSION = {v1},
}