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* add char-based pruned-rnnt2 for wenetspeech * style check * style check * change for export.py * do some changes * do some changes * a small change for .flake8 * solve the conflicts
20 lines
903 B
Markdown
20 lines
903 B
Markdown
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# Introduction
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This recipe includes some different ASR models trained with WenetSpeech.
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[./RESULTS.md](./RESULTS.md) contains the latest results.
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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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| `pruned_transducer_stateless2` | Conformer(modified) | Embedding + Conv1d | Using k2 pruned RNN-T loss | |
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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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