upload the decoding results of rnn-lm to the RESULTS

This commit is contained in:
Quandwang 2022-07-22 15:15:53 +08:00
parent 79d7c94397
commit d71e35d85e
2 changed files with 5 additions and 5 deletions

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@ -10,7 +10,8 @@ per-file-ignores =
egs/*/ASR/*/optim.py: E501, egs/*/ASR/*/optim.py: E501,
egs/*/ASR/*/scaling.py: E501, egs/*/ASR/*/scaling.py: E501,
egs/librispeech/ASR/conv_emformer_transducer_stateless*/*.py: E501, E203, egs/librispeech/ASR/conv_emformer_transducer_stateless*/*.py: E501, E203,
egs/librispeech/ASR/conformer_ctc2/*py: E501 egs/librispeech/ASR/conformer_ctc2/*py: E501,
egs/librispeech/ASR/RESULTS.md: E999,
# invalid escape sequence (cause by tex formular), W605 # invalid escape sequence (cause by tex formular), W605
icefall/utils.py: E501, W605 icefall/utils.py: E501, W605

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@ -1,6 +1,6 @@
## Results ## Results
### LibriSpeech BPE training results (Pruned Stateless Conv-Emformer RNN-T 2) #### LibriSpeech BPE training results (Pruned Stateless Conv-Emformer RNN-T 2)
[conv_emformer_transducer_stateless2](./conv_emformer_transducer_stateless2) [conv_emformer_transducer_stateless2](./conv_emformer_transducer_stateless2)
@ -1998,10 +1998,9 @@ avg=11
You can find the tensorboard log at: <https://tensorboard.dev/experiment/D7NQc3xqTpyVmWi5FnWjrA> You can find the tensorboard log at: <https://tensorboard.dev/experiment/D7NQc3xqTpyVmWi5FnWjrA>
### LibriSpeech BPE training results (Conformer-CTC 2) ### LibriSpeech BPE training results (Conformer-CTC 2)
[conformer_ctc2](./conformer_ctc2) #### [conformer_ctc2](./conformer_ctc2)
#### 2022-07-21 #### 2022-07-21
@ -2037,7 +2036,7 @@ The decoding configuration for the reworked model is --epoch 30, --avg 8, --use-
| whole-lattice-rescoring| 2.66% | 5.76%| 4.21%| 2.56%| 6.04%| 4.30%| | whole-lattice-rescoring| 2.66% | 5.76%| 4.21%| 2.56%| 6.04%| 4.30%|
| attention-decoder | 2.59% | 5.54%| 4.07%| 2.41%| 5.77%| 4.09%| | attention-decoder | 2.59% | 5.54%| 4.07%| 2.41%| 5.77%| 4.09%|
| nbest-oracle | 1.53% | 3.47%| 2.50%| 1.69%| 4.02%| 2.86%| | nbest-oracle | 1.53% | 3.47%| 2.50%| 1.69%| 4.02%| 2.86%|
|rnn-lm | 2.37% | 4.98%| 3.68%| 2.31%| 5.35%| 3.83%| | rnn-lm | 2.37% | 4.98%| 3.68%| 2.31%| 5.35%| 3.83%|