Wav2vec 2.0 model (“base” architecture with an extra linear module), pre-trained on 960 hours of unlabeled audio from LibriSpeech dataset [Panayotov et al., 2015] (the combination of “train-clean-100”, “train-clean-360”, and “train-other-500”), and fine-tuned for ASR on 100 hours of transcribed audio from “train-clean-100” subset.
Originally published by the authors of wav2vec 2.0 [Baevski et al., 2020] under MIT License and redistributed with the same license. [License, Source]
Please refer to
torchaudio.pipelines.Wav2Vec2ASRBundlefor the usage.