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* pruned-rnnt5-for-wenetspeech * style check * style check * add streaming conformer * add streaming decode * changes codes for fast_beam_search and export cpu jit * add modified-beam-search for streaming decoding * add modified-beam-search for streaming decoding * change for streaming_beam_search.py * add README.md and RESULTS.md * change for style_check.yml * do some changes * do some changes for export.py * add some decode commands for usage * add streaming results on README.md
21 lines
1.0 KiB
Markdown
21 lines
1.0 KiB
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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| `pruned_transducer_stateless5` | 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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