Edresson/Wav2Vec-Wrapper

An easy way to fine-tune Wav2Vec 2.0 for low-resource languages. # Wav2Vec-Wrapper An easy way to fine-tune Wav2Vec 2.0 for low-resource languages. ## Pretrained Models and Reproducibility | Paper | Description | Instructions | |---------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------| | CORAA | Checkpoints for the paper: "CORAA: a large corpus of spontaneous and prepared speech manually validated for speech recognition in Brazilian Portuguese". More details here | link | | SE&R-Challenge | Fine-tuning instructions for the ASR for Spontaneous and Prepared Speech, and Speech Emotion Recognition Shared task. More details here | link | | YourTTS2ASR | Checkpoints for the paper: "ASR data augmentation in low-resource settings using cross-lingual multi-speaker TTS and cross-lingual voice conversion". More details here | link | # Installation Clone the repository. ```bash git clone github.com pip3 install -r requeriments.txt ``` ## Install Flashlight dependencies to use KenLM ### Use Docker: In the Wav2Vec-Wrapper repository execute: ``` nvidia-docker build ./ -t huggingface_flashlight ``` Now see the id of the docker image you just created: ``` docker images ``` Using the IMAGE_ID run the command: …