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wav2vec 2.0: A Framework for Self-supervised Learning of Speech Representations

This is not an official implementation, but a modified version of wav2vec 2.0: A Framework for Self-supervised Learning of Speech Representations to apply to ECG domain, instead of audio.

Before training the model, please follow these instructions to install fairseq-signals and prepare required datasets.

Pre-training a new model

$ fairseq-hydra-train \
    task.data=/path/to/manifest/pretrain \
    --config-dir examples/wav2vec2/config/pretraining \
    --config-name w2v

If you want to apply some augmentations while training the model, refer to examples/wav2vec2/pretraining/w2v_augs.yaml.

Fine-tuning a pre-trained model

Fine-tune on the Cardiac Arrhythmia Classification task

$ fairseq-hydra-train \
    task.data=/path/to/manifest/finetune \
    model.model_path=/path/to/checkpoint.pt \
    --config-dir examples/wav2vec2/config/finetuning \
    --config-name diagnosis

If you want to use CinC score as an evaluation metric, add command line parameters (before --config-dir) criterion.report_cinc_score=True criterion.weights_file=/path/to/weights.csv

Note that you can download weights.csv file from here.

Fine-tune on the Patient Identification task

$ fairseq-hydra-train \
    task.data=/path/to/manifest/identify \
    model.model_path=/path/to/checkpoint.pt \
    model.num_labels=$N \
    --config-dir examples/wav2vec2/config/finetuning \
    --config-name identification

$N should be set to the number of unique patients in the training dataset. You can manually open /path/to/manifest/identify/train.tsv file and check the last line of that file. For example, if the last line is like *.mat 2500 69977, then $N should be set to 69978.

Note that if you want to train with PhysioNet2021 dataset and test with PTB-XL dataset, prepare data manifest for PhysioNet2021 with $valid=0 and PTB-XL with $valid=1.0 seperately and place them to the same manifest directory like this:

path/to/manifest/identify
├─ train.tsv
├─ valid_gallery.tsv
└─ valid_probe.tsv

Note: valid_*.tsv should have been from PTB-XL dataset while train.tsv should have been from PhysioNet2021 dataset.