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* Copy files for editing. * Use librispeech + gigaspeech with modified conformer. * Support specifying number of workers for on-the-fly feature extraction. * Feature extraction code for GigaSpeech. * Combine XL splits lazily during training. * Fix warnings in decoding. * Add decoding code for GigaSpeech. * Fix decoding the gigaspeech dataset. We have to use the decoder/joiner networks for the GigaSpeech dataset. * Disable speed perturbe for XL subset. * Compute the Nbest oracle WER for RNN-T decoding. * Minor fixes. * Minor fixes. * Add results. * Update results. * Update CI. * Update results. * Fix style issues. * Update results. * Fix style issues.
22 lines
1.9 KiB
Markdown
22 lines
1.9 KiB
Markdown
# Introduction Please refer to <https://icefall.readthedocs.io/en/latest/recipes/librispeech/index.html> for how to run models in this recipe.
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# Transducers
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There are various folders containing the name `transducer` in this folder.
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The following table lists the differences among them.
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| | Encoder | Decoder | Comment |
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|---------------------------------------|---------------------|--------------------|---------------------------------------------------|
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| `transducer` | Conformer | LSTM | |
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| `transducer_stateless` | Conformer | Embedding + Conv1d | Using optimized_transducer from computing RNN-T loss |
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| `transducer_stateless2` | Conformer | Embedding + Conv1d | Using torchaudio for computing RNN-T loss |
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| `transducer_lstm` | LSTM | LSTM | |
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| `transducer_stateless_multi_datasets` | Conformer | Embedding + Conv1d | Using data from GigaSpeech as extra training data |
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| `pruned_transducer_stateless` | Conformer | Embedding + Conv1d | Using k2 pruned RNN-T loss |
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| `pruned_transducer_stateless2` | Conformer(modified) | Embedding + Conv1d | Using k2 pruned RNN-T loss |
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| `pruned_transducer_stateless3` | Conformer(modified) | Embedding + Conv1d | Using k2 pruned RNN-T loss + using GigaSpeech as extra training data |
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The decoder in `transducer_stateless` is modified from the paper
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[Rnn-Transducer with Stateless Prediction Network](https://ieeexplore.ieee.org/document/9054419/).
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We place an additional Conv1d layer right after the input embedding layer.
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