[Ready to merge] Pruned Transducer Stateless2 for WenetSpeech (char-based) #349
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luomingshuang
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The best results trained with L subset (better than other public results at present):
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luomingshuang
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README.md
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| @@ -20,6 +20,11 @@ We provide 6 recipes at present: | |||
| - [TIMIT][timit] | |||
| - [TED-LIUM3][tedlium3] | |||
| - [GigaSpeech][gigaspeech] | |||
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Please resolve the conflicts.
| | fast beam search (set as default) | 19.31 | 24.41 | 34.87 | --epoch 29, --avg 24, --max-duration 1500 | | ||
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| A pre-trained model and decoding logs can be found at <https://huggingface.co/luomingshuang/icefall_asr_wenetspeech_pruned_transducer_stateless2> |
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Could you also add the pretrained models and decoding results for the M and S subset to huggingface?
Also, could you upload the training logs to huggingface?
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OK, no problem.
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Thanks! |
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@luomingshuang how long it takes to complete wenetspeech training with L set? |
| --training-subset L | ||
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| The tensorboard training log can be found at |
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You can find the tensorboard log here. And according to this log, it takes about 21 days 16 hours and a half for 17 epochs. According to my results, I think it can be stopped when training for 11 epochs.
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tks |
Actually, there is an existing PR #314 with pruned transducer stateless2 for wenetspeech. But that PR can be regarded as a draft. This PR aims to merge into the master. Of course, the process trained with the L subset is still going on. (The results are better than other methods at present. And the performance still gets a little improvement. I will update the results on RESULT.md) It doesn't influence the code review for this PR. The greedy_search_new and modified_beam_search_new are from the PR #358.
Results: