metadata

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

CRDNN 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. The given ASR model performance are:

Release	Test CER	Test WER	GPUs
29-04-21	6.54	13.90	2xV100 32GB

Pipeline description

This ASR system is composed of 2 different but linked blocks:

Tokenizer (unigram) that transforms words into subword units and trained with the train transcriptions (train.tsv) of CommonVoice (FR).
Acoustic model (wav2vec2.0 + CTC/Attention). A pretrained wav2vec 2.0 model (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.

Transcribing your own audio files (in French)

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}},
  }