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- Introduce unified AMP helpers (create_grad_scaler, torch_autocast) to handle deprecations in PyTorch ≥2.3.0 - Replace direct uses of torch.cuda.amp.GradScaler and torch.cuda.amp.autocast with the new utilities across all training and inference scripts - Update all torch.load calls to include weights_only=False for compatibility with newer PyTorch versions
GigaSpeech
GigaSpeech, an evolving, multi-domain English speech recognition corpus with 10,000 hours of high quality labeled audio, collected from audiobooks, podcasts and YouTube, covering both read and spontaneous speaking styles, and a variety of topics, such as arts, science, sports, etc. More details can be found: https://github.com/SpeechColab/GigaSpeech
Download
Apply for the download credentials and download the dataset by following https://github.com/SpeechColab/GigaSpeech#download. Then create a symlink
ln -sfv /path/to/GigaSpeech download/GigaSpeech
Performance Record
Dev | Test | |
---|---|---|
zipformer |
10.25 | 10.38 |
conformer_ctc |
10.47 | 10.58 |
pruned_transducer_stateless2 |
10.40 | 10.51 |
See RESULTS for details.