1. 21 Apr, 2022 1 commit
    • hwangjeff's avatar
      Change underlying implementation of RNN-T hypothesis to tuple (#2339) · 6b242c29
      hwangjeff authored
      Summary:
      PyTorch Lite, which is becoming a standard for mobile PyTorch usage, does not support containers containing custom classes. Consequently, because TorchAudio's RNN-T decoder currently returns and accepts lists of `Hypothesis` namedtuples, it is not compatible with PyTorch Lite. This PR resolves said incompatibility by changing the underlying implementation of `Hypothesis` to tuple.
      
      Pull Request resolved: https://github.com/pytorch/audio/pull/2339
      
      Reviewed By: nateanl
      
      Differential Revision: D35806529
      
      Pulled By: hwangjeff
      
      fbshipit-source-id: 9cbae5504722390511d35e7f9966af2519ccede5
      6b242c29
  2. 13 Apr, 2022 1 commit
    • hwangjeff's avatar
      Add Conformer RNN-T LibriSpeech training recipe (#2329) · c262758b
      hwangjeff authored
      Summary:
      Adds Conformer RNN-T LibriSpeech training recipe to examples directory.
      
      Produces 30M-parameter model that achieves the following WER:
      
      |                     |          WER |
      |:-------------------:|-------------:|
      | test-clean          |       0.0310 |
      | test-other          |       0.0805 |
      | dev-clean           |       0.0314 |
      | dev-other           |       0.0827 |
      
      Pull Request resolved: https://github.com/pytorch/audio/pull/2329
      
      Reviewed By: xiaohui-zhang
      
      Differential Revision: D35578727
      
      Pulled By: hwangjeff
      
      fbshipit-source-id: afa9146c5b647727b8605d104d928110a1d3976d
      c262758b