import from zenodo
Browse files- README.md +50 -0
- exp/asr_stats_raw/train/feats_stats.npz +0 -0
- exp/asr_train_asr_transformer_raw_char/RESULTS.md +37 -0
- exp/asr_train_asr_transformer_raw_char/config.yaml +207 -0
- exp/asr_train_asr_transformer_raw_char/images/acc.png +0 -0
- exp/asr_train_asr_transformer_raw_char/images/backward_time.png +0 -0
- exp/asr_train_asr_transformer_raw_char/images/cer.png +0 -0
- exp/asr_train_asr_transformer_raw_char/images/cer_ctc.png +0 -0
- exp/asr_train_asr_transformer_raw_char/images/forward_time.png +0 -0
- exp/asr_train_asr_transformer_raw_char/images/iter_time.png +0 -0
- exp/asr_train_asr_transformer_raw_char/images/loss.png +0 -0
- exp/asr_train_asr_transformer_raw_char/images/loss_att.png +0 -0
- exp/asr_train_asr_transformer_raw_char/images/loss_ctc.png +0 -0
- exp/asr_train_asr_transformer_raw_char/images/lr_0.png +0 -0
- exp/asr_train_asr_transformer_raw_char/images/optim_step_time.png +0 -0
- exp/asr_train_asr_transformer_raw_char/images/train_time.png +0 -0
- exp/asr_train_asr_transformer_raw_char/images/wer.png +0 -0
- exp/asr_train_asr_transformer_raw_char/valid.acc.ave_10best.pth +3 -0
- exp/lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4/40epoch.pth +3 -0
- exp/lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4/config.yaml +166 -0
- exp/lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4/images/backward_time.png +0 -0
- exp/lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4/images/forward_time.png +0 -0
- exp/lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4/images/iter_time.png +0 -0
- exp/lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4/images/loss.png +0 -0
- exp/lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4/images/lr_0.png +0 -0
- exp/lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4/images/optim_step_time.png +0 -0
- exp/lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4/images/train_time.png +0 -0
- exp/lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4/perplexity_test/ppl +1 -0
- meta.yaml +10 -0
README.md
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---
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tags:
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- espnet
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- audio
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- automatic-speech-recognition
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language: en
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datasets:
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- wsj
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license: cc-by-4.0
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---
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## Example ESPnet2 ASR model
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### `kamo-naoyuki/wsj`
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♻️ Imported from https://zenodo.org/record/4003381/
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This model was trained by kamo-naoyuki using wsj/asr1 recipe in [espnet](https://github.com/espnet/espnet/).
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### Demo: How to use in ESPnet2
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```python
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# coming soon
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```
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### Citing ESPnet
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```BibTex
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@inproceedings{watanabe2018espnet,
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author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
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title={{ESPnet}: End-to-End Speech Processing Toolkit},
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year={2018},
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booktitle={Proceedings of Interspeech},
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pages={2207--2211},
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doi={10.21437/Interspeech.2018-1456},
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url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
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}
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@inproceedings{hayashi2020espnet,
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title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
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author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
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booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
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pages={7654--7658},
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year={2020},
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organization={IEEE}
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}
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```
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or arXiv:
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```bibtex
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@misc{watanabe2018espnet,
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title={ESPnet: End-to-End Speech Processing Toolkit},
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author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
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year={2018},
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eprint={1804.00015},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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exp/asr_stats_raw/train/feats_stats.npz
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Binary file (1.4 kB). View file
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exp/asr_train_asr_transformer_raw_char/RESULTS.md
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<!-- Generated by scripts/utils/show_asr_result.sh -->
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# RESULTS
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## Environments
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- date: `Thu Aug 27 09:50:23 JST 2020`
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- python version: `3.7.3 (default, Mar 27 2019, 22:11:17) [GCC 7.3.0]`
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- espnet version: `espnet 0.9.0`
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- pytorch version: `pytorch 1.6.0`
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- Git hash: `4b040785069f114fe046ffa9acdd8698fdeb7f21`
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- Commit date: `Tue Aug 25 17:46:25 2020 +0900`
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## asr_train_asr_transformer_raw_char
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### WER
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|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
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|---|---|---|---|---|---|---|---|---|
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|inference_lm_lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4_valid.loss.ave_asr_model_valid.acc.ave/test_dev93|503|8234|93.3|5.9|0.8|0.8|7.5|58.1|
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+
|inference_lm_lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4_valid.loss.ave_asr_model_valid.acc.ave/test_eval92|333|5643|95.8|4.0|0.3|0.7|5.0|44.7|
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|inference_lm_lm_train_lm_char_optimadam_optim_conflr0.0005_lm_confnlayers4_keep_nbest_models235810_batch_size512_valid.loss.ave_asr_model_valid.acc.ave/test_dev93|503|8234|93.2|5.9|0.8|0.9|7.6|59.0|
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|inference_lm_lm_train_lm_char_optimadam_optim_conflr0.0005_lm_confnlayers4_keep_nbest_models235810_batch_size512_valid.loss.ave_asr_model_valid.acc.ave/test_eval92|333|5643|95.8|4.0|0.2|0.7|4.9|45.6|
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+
|inference_lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4_valid.loss.best_asr_model_valid.acc.best/test_dev93|503|8234|92.3|6.8|1.0|1.0|8.8|62.2|
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|inference_lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4_valid.loss.best_asr_model_valid.acc.best/test_eval92|333|5643|94.8|4.8|0.5|0.9|6.1|48.6|
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+
|inference_lm_train_lm_char_valid.loss.best_asr_model_valid.acc.best/test_dev93|503|8234|80.9|17.4|1.7|2.6|21.7|90.7|
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|inference_lm_train_lm_char_valid.loss.best_asr_model_valid.acc.best/test_eval92|333|5643|84.3|14.6|1.1|2.4|18.1|86.8|
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+
|
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### CER
|
26 |
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|
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|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
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|---|---|---|---|---|---|---|---|---|
|
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+
|inference_lm_lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4_valid.loss.ave_asr_model_valid.acc.ave/test_dev93|503|48634|97.6|1.1|1.3|0.6|3.0|62.8|
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+
|inference_lm_lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4_valid.loss.ave_asr_model_valid.acc.ave/test_eval92|333|33341|98.5|0.7|0.8|0.5|2.0|53.2|
|
31 |
+
|inference_lm_lm_train_lm_char_optimadam_optim_conflr0.0005_lm_confnlayers4_keep_nbest_models235810_batch_size512_valid.loss.ave_asr_model_valid.acc.ave/test_dev93|503|48634|97.5|1.2|1.3|0.5|3.1|63.6|
|
32 |
+
|inference_lm_lm_train_lm_char_optimadam_optim_conflr0.0005_lm_confnlayers4_keep_nbest_models235810_batch_size512_valid.loss.ave_asr_model_valid.acc.ave/test_eval92|333|33341|98.5|0.7|0.8|0.5|2.0|53.2|
|
33 |
+
|inference_lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4_valid.loss.best_asr_model_valid.acc.best/test_dev93|503|48634|97.0|1.4|1.6|0.7|3.6|67.2|
|
34 |
+
|inference_lm_train_lm_char_optimadam_batch_size512_optim_conflr0.0005_lm_confnlayers4_valid.loss.best_asr_model_valid.acc.best/test_eval92|333|33341|98.0|0.9|1.0|0.5|2.5|56.8|
|
35 |
+
|inference_lm_train_lm_char_valid.loss.best_asr_model_valid.acc.best/test_dev93|503|48634|94.4|2.8|2.9|1.5|7.1|91.3|
|
36 |
+
|inference_lm_train_lm_char_valid.loss.best_asr_model_valid.acc.best/test_eval92|333|33341|95.6|2.2|2.1|1.3|5.7|88.9|
|
37 |
+
|
exp/asr_train_asr_transformer_raw_char/config.yaml
ADDED
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config: conf/train_asr_transformer.yaml
|
2 |
+
print_config: false
|
3 |
+
log_level: INFO
|
4 |
+
dry_run: false
|
5 |
+
iterator_type: sequence
|
6 |
+
output_dir: exp/asr_train_asr_transformer_raw_char
|
7 |
+
ngpu: 1
|
8 |
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seed: 0
|
9 |
+
num_workers: 1
|
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num_att_plot: 3
|
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dist_backend: nccl
|
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dist_init_method: env://
|
13 |
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dist_world_size: null
|
14 |
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dist_rank: null
|
15 |
+
local_rank: 0
|
16 |
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dist_master_addr: null
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dist_master_port: null
|
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dist_launcher: null
|
19 |
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multiprocessing_distributed: false
|
20 |
+
cudnn_enabled: true
|
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cudnn_benchmark: false
|
22 |
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cudnn_deterministic: true
|
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collect_stats: false
|
24 |
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write_collected_feats: false
|
25 |
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max_epoch: 100
|
26 |
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patience: null
|
27 |
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val_scheduler_criterion:
|
28 |
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- valid
|
29 |
+
- loss
|
30 |
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early_stopping_criterion:
|
31 |
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- valid
|
32 |
+
- loss
|
33 |
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- min
|
34 |
+
best_model_criterion:
|
35 |
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- - valid
|
36 |
+
- acc
|
37 |
+
- max
|
38 |
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keep_nbest_models: 10
|
39 |
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grad_clip: 5.0
|
40 |
+
grad_noise: false
|
41 |
+
accum_grad: 8
|
42 |
+
no_forward_run: false
|
43 |
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resume: true
|
44 |
+
train_dtype: float32
|
45 |
+
use_amp: false
|
46 |
+
log_interval: null
|
47 |
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pretrain_path: []
|
48 |
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pretrain_key: []
|
49 |
+
num_iters_per_epoch: null
|
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batch_size: 32
|
51 |
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valid_batch_size: null
|
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batch_bins: 1000000
|
53 |
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valid_batch_bins: null
|
54 |
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train_shape_file:
|
55 |
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- exp/asr_stats_raw/train/speech_shape
|
56 |
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- exp/asr_stats_raw/train/text_shape.char
|
57 |
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valid_shape_file:
|
58 |
+
- exp/asr_stats_raw/valid/speech_shape
|
59 |
+
- exp/asr_stats_raw/valid/text_shape.char
|
60 |
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batch_type: folded
|
61 |
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valid_batch_type: null
|
62 |
+
fold_length:
|
63 |
+
- 80000
|
64 |
+
- 150
|
65 |
+
sort_in_batch: descending
|
66 |
+
sort_batch: descending
|
67 |
+
multiple_iterator: false
|
68 |
+
chunk_length: 500
|
69 |
+
chunk_shift_ratio: 0.5
|
70 |
+
num_cache_chunks: 1024
|
71 |
+
train_data_path_and_name_and_type:
|
72 |
+
- - dump/raw/train_si284/wav.scp
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73 |
+
- speech
|
74 |
+
- sound
|
75 |
+
- - dump/raw/train_si284/text
|
76 |
+
- text
|
77 |
+
- text
|
78 |
+
valid_data_path_and_name_and_type:
|
79 |
+
- - dump/raw/test_dev93/wav.scp
|
80 |
+
- speech
|
81 |
+
- sound
|
82 |
+
- - dump/raw/test_dev93/text
|
83 |
+
- text
|
84 |
+
- text
|
85 |
+
allow_variable_data_keys: false
|
86 |
+
max_cache_size: 0.0
|
87 |
+
valid_max_cache_size: null
|
88 |
+
optim: adam
|
89 |
+
optim_conf:
|
90 |
+
lr: 0.005
|
91 |
+
scheduler: warmuplr
|
92 |
+
scheduler_conf:
|
93 |
+
warmup_steps: 30000
|
94 |
+
token_list:
|
95 |
+
- <blank>
|
96 |
+
- <unk>
|
97 |
+
- <space>
|
98 |
+
- E
|
99 |
+
- T
|
100 |
+
- A
|
101 |
+
- N
|
102 |
+
- I
|
103 |
+
- O
|
104 |
+
- S
|
105 |
+
- R
|
106 |
+
- H
|
107 |
+
- L
|
108 |
+
- D
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109 |
+
- C
|
110 |
+
- U
|
111 |
+
- M
|
112 |
+
- P
|
113 |
+
- F
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