import from zenodo
Browse files- README.md +43 -0
- data/token_list/bpe_unigram1000/bpe.model +3 -0
- exp/asr_stats_raw_bpe1000/train/feats_stats.npz +0 -0
- exp/asr_train_asr_raw_bpe1000/RESULTS.md +35 -0
- exp/asr_train_asr_raw_bpe1000/config.yaml +1155 -0
- exp/asr_train_asr_raw_bpe1000/images/acc.png +0 -0
- exp/asr_train_asr_raw_bpe1000/images/backward_time.png +0 -0
- exp/asr_train_asr_raw_bpe1000/images/cer.png +0 -0
- exp/asr_train_asr_raw_bpe1000/images/cer_ctc.png +0 -0
- exp/asr_train_asr_raw_bpe1000/images/forward_time.png +0 -0
- exp/asr_train_asr_raw_bpe1000/images/iter_time.png +0 -0
- exp/asr_train_asr_raw_bpe1000/images/loss.png +0 -0
- exp/asr_train_asr_raw_bpe1000/images/loss_att.png +0 -0
- exp/asr_train_asr_raw_bpe1000/images/loss_ctc.png +0 -0
- exp/asr_train_asr_raw_bpe1000/images/lr_0.png +0 -0
- exp/asr_train_asr_raw_bpe1000/images/optim_step_time.png +0 -0
- exp/asr_train_asr_raw_bpe1000/images/train_time.png +0 -0
- exp/asr_train_asr_raw_bpe1000/images/wer.png +0 -0
- exp/asr_train_asr_raw_bpe1000/valid.acc.best.pth +3 -0
- meta.yaml +8 -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: jv
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datasets:
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- jv_openslr35
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license: cc-by-4.0
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---
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## ESPnet2 ASR pretrained model
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### `jv_openslr35`
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♻️ Imported from https://zenodo.org/record/5090139/
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This model was trained by jv_openslr35 using jv_openslr35/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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```
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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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data/token_list/bpe_unigram1000/bpe.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:5d60cd15af7163345f662b25b17988d253b82d74a00d813249d0443133917811
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size 252887
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exp/asr_stats_raw_bpe1000/train/feats_stats.npz
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Binary file (1.4 kB). View file
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exp/asr_train_asr_raw_bpe1000/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: `Fri Jul 9 17:56:55 PDT 2021`
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- python version: `3.8.5 (default, Sep 4 2020, 07:30:14) [GCC 7.3.0]`
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- espnet version: `espnet 0.10.0`
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- pytorch version: `pytorch 1.8.1+cu102`
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- Git hash: `5830a6b49a60ae10b8c113a2b9635ec2273fbdab`
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- Commit date: `Fri Jul 9 08:36:41 2021 -0700`
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## asr_train_asr_raw_bpe1000
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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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|decode_asr_batch_size1_asr_model_valid.acc.best/dev_iban|473|11006|2.5|54.0|43.5|0.1|97.7|100.0|
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|decode_asr_batch_size1_asr_model_valid.acc.best/java_test|1740|12117|81.9|16.4|1.7|0.9|19.0|52.3|
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|decode_asr_batch_size1_asr_model_valid.acc.best/test_id_commonvoice|1643|9565|15.7|69.4|14.9|3.3|87.6|99.9|
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### CER
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|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
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|---|---|---|---|---|---|---|---|---|
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|decode_asr_batch_size1_asr_model_valid.acc.best/dev_iban|473|67025|53.0|17.6|29.3|5.4|52.3|100.0|
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|decode_asr_batch_size1_asr_model_valid.acc.best/java_test|1740|80419|95.4|2.6|2.0|0.8|5.4|52.3|
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|decode_asr_batch_size1_asr_model_valid.acc.best/test_id_commonvoice|1643|61563|69.4|14.3|16.3|5.0|35.6|99.9|
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### TER
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|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
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|---|---|---|---|---|---|---|---|---|
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|decode_asr_batch_size1_asr_model_valid.acc.best/dev_iban|473|22012|1.2|96.4|2.4|12.1|110.8|100.0|
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|decode_asr_batch_size1_asr_model_valid.acc.best/java_test|1740|26604|84.6|10.6|4.8|1.2|16.6|52.3|
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|decode_asr_batch_size1_asr_model_valid.acc.best/test_id_commonvoice|1643|27446|39.7|42.0|18.3|3.1|63.5|99.9|
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exp/asr_train_asr_raw_bpe1000/config.yaml
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|
1 |
+
config: conf/train_asr.yaml
|
2 |
+
print_config: false
|
3 |
+
log_level: INFO
|
4 |
+
dry_run: false
|
5 |
+
iterator_type: sequence
|
6 |
+
output_dir: exp/asr_train_asr_raw_bpe1000
|
7 |
+
ngpu: 1
|
8 |
+
seed: 0
|
9 |
+
num_workers: 1
|
10 |
+
num_att_plot: 3
|
11 |
+
dist_backend: nccl
|
12 |
+
dist_init_method: env://
|
13 |
+
dist_world_size: null
|
14 |
+
dist_rank: null
|
15 |
+
local_rank: 0
|
16 |
+
dist_master_addr: null
|
17 |
+
dist_master_port: null
|
18 |
+
dist_launcher: null
|
19 |
+
multiprocessing_distributed: false
|
20 |
+
cudnn_enabled: true
|
21 |
+
cudnn_benchmark: false
|
22 |
+
cudnn_deterministic: true
|
23 |
+
collect_stats: false
|
24 |
+
write_collected_feats: false
|
25 |
+
max_epoch: 200
|
26 |
+
patience: 20
|
27 |
+
val_scheduler_criterion:
|
28 |
+
- valid
|
29 |
+
- loss
|
30 |
+
early_stopping_criterion:
|
31 |
+
- valid
|
32 |
+
- loss
|
33 |
+
- min
|
34 |
+
best_model_criterion:
|
35 |
+
- - valid
|
36 |
+
- acc
|
37 |
+
- max
|
38 |
+
keep_nbest_models: 10
|
39 |
+
grad_clip: 5
|
40 |
+
grad_clip_type: 2.0
|
41 |
+
grad_noise: false
|
42 |
+
accum_grad: 2
|
43 |
+
no_forward_run: false
|
44 |
+
resume: true
|
45 |
+
train_dtype: float32
|
46 |
+
use_amp: false
|
47 |
+
log_interval: null
|
48 |
+
unused_parameters: false
|
49 |
+
use_tensorboard: true
|
50 |
+
use_wandb: false
|
51 |
+
wandb_project: null
|
52 |
+
wandb_id: null
|
53 |
+
pretrain_path: null
|
54 |
+
init_param: []
|
55 |
+
freeze_param: []
|
56 |
+
num_iters_per_epoch: null
|
57 |
+
batch_size: 32
|
58 |
+
valid_batch_size: null
|
59 |
+
batch_bins: 1000000
|
60 |
+
valid_batch_bins: null
|
61 |
+
train_shape_file:
|
62 |
+
- exp/asr_stats_raw_bpe1000/train/speech_shape
|
63 |
+
- exp/asr_stats_raw_bpe1000/train/text_shape.bpe
|
64 |
+
valid_shape_file:
|
65 |
+
- exp/asr_stats_raw_bpe1000/valid/speech_shape
|
66 |
+
- exp/asr_stats_raw_bpe1000/valid/text_shape.bpe
|
67 |
+
batch_type: folded
|
68 |
+
valid_batch_type: null
|
69 |
+
fold_length:
|
70 |
+
- 80000
|
71 |
+
- 150
|
72 |
+
sort_in_batch: descending
|
73 |
+
sort_batch: descending
|
74 |
+
multiple_iterator: false
|
75 |
+
chunk_length: 500
|
76 |
+
chunk_shift_ratio: 0.5
|
77 |
+
num_cache_chunks: 1024
|
78 |
+
train_data_path_and_name_and_type:
|
79 |
+
- - dump/raw/java_train/wav.scp
|
80 |
+
- speech
|
81 |
+
- sound
|
82 |
+
- - dump/raw/java_train/text
|
83 |
+
- text
|
84 |
+
- text
|
85 |
+
valid_data_path_and_name_and_type:
|
86 |
+
- - dump/raw/java_dev/wav.scp
|
87 |
+
- speech
|
88 |
+
- sound
|
89 |
+
- - dump/raw/java_dev/text
|
90 |
+
- text
|
91 |
+
- text
|
92 |
+
allow_variable_data_keys: false
|
93 |
+
max_cache_size: 0.0
|
94 |
+
max_cache_fd: 32
|
95 |
+
valid_max_cache_size: null
|
96 |
+
optim: adam
|
97 |
+
optim_conf:
|
98 |
+
lr: 10.0
|
99 |
+
scheduler: noamlr
|
100 |
+
scheduler_conf:
|
101 |
+
warmup_steps: 25000
|
102 |
+
token_list:
|
103 |
+
- <blank>
|
104 |
+
- <unk>
|
105 |
+
- NG
|
106 |
+
- E
|
107 |
+
- S
|
108 |
+
- I
|
109 |
+
- H
|
110 |
+
- N
|
111 |
+
- ▁
|
112 |
+
- K
|
113 |
+
- T
|
114 |
+
- L
|
115 |
+
- R
|
116 |
+
- ▁DI
|
117 |
+
- AN
|
118 |
+
- M
|
119 |
+
- É
|
120 |
+
- ▁A
|
121 |
+
- ▁ING
|
122 |
+
- A
|
123 |
+
- NA
|
124 |
+
- NE
|
125 |
+
- TA
|
126 |
+
- P
|
127 |
+
- D
|
128 |
+
- Y
|
129 |
+
- RA
|
130 |
+
- LA
|
131 |
+
- ▁KA
|
132 |
+
- SI
|
133 |
+
- ▁KARO
|
134 |
+
- U
|
135 |
+
- TI
|
136 |
+
- ▁LAN
|
137 |
+
- RI
|
138 |
+
- KA
|
139 |
+
- MA
|
140 |
+
- ▁MA
|
141 |
+
- ▁DHATENG
|
142 |
+
- ▁IKU
|
143 |
+
- ▁LUNGA
|
144 |
+
- YA
|
145 |
+
- ▁SA
|
146 |
+
- SA
|
147 |
+
- NI
|
148 |
+
- O
|
149 |
+
- ▁MENYA
|
150 |
+
- G
|
151 |
+
- WA
|
152 |
+
- ▁DOLAN
|
153 |
+
- ▁KE
|
154 |
+
- LI
|
155 |
+
- ▁SE
|
156 |
+
- DA
|
157 |
+
- GA
|
158 |
+
- ▁IKI
|
159 |
+
- ▁PA
|
160 |
+
- ▁SAK
|
161 |
+
- ▁S
|
162 |
+
- LE
|
163 |
+
- B
|
164 |
+
- JRONING
|
165 |
+
- ▁BA
|
166 |
+
- ▁KANG
|
167 |
+
- DI
|
168 |
+
- ▁TANSA
|
169 |
+
- JA
|
170 |
+
- RE
|
171 |
+
- BA
|
172 |
+
- ▁ELING
|
173 |
+
- PA
|
174 |
+
- ▁RA
|
175 |
+
- ▁DIWUJUDK
|
176 |
+
- ▁IMPI
|
177 |
+
- TU
|
178 |
+
- ▁PUNIKA
|
179 |
+
- ▁SU
|
180 |
+
- ▁I
|
181 |
+
- NÉ
|
182 |
+
- RO
|
183 |
+
- ▁ANA
|
184 |
+
- ▁ME
|
185 |
+
- ▁TA
|
186 |
+
- MI
|
187 |
+
- F
|
188 |
+
- TE
|
189 |
+
- KU
|
190 |
+
- TO
|
191 |
+
- 'ON'
|
192 |
+
- RU
|
193 |
+
- ▁SING
|
194 |
+
- ▁PE
|
195 |
+
- IPUN
|
196 |
+
- BU
|
197 |
+
- ▁SI
|
198 |
+
- ▁LA
|
199 |
+
- EN
|
200 |
+
- ▁KERJA
|
201 |
+
- ▁E
|
202 |
+
- LO
|
203 |
+
- GI
|
204 |
+
- IN
|
205 |
+
- KONTRAK
|
206 |
+
- ▁B
|
207 |
+
- ▁O
|
208 |
+
- CA
|
209 |
+
- ▁UGA
|
210 |
+
- ER
|
211 |
+
- ▁SAKA
|
212 |
+
- ▁DADI
|
213 |
+
- ▁T
|
214 |
+
- TAN
|
215 |
+
- È
|
216 |
+
- C
|
217 |
+
- ▁YA
|
218 |
+
- ▁U
|
219 |
+
- WI
|
220 |
+
- ▁NA
|
221 |
+
- ▁C
|
222 |
+
- ▁KU
|
223 |
+
- LU
|
224 |
+
- ▁K
|
225 |
+
- ▁RE
|
226 |
+
- ▁JA
|
227 |
+
- ▁PER
|
228 |
+
- ▁WA
|
229 |
+
- ▁MI
|
230 |
+
- RAN
|
231 |
+
- MAN
|
232 |
+
- AL
|
233 |
+
- US
|
234 |
+
- EL
|
235 |
+
- ▁UNIVERSITY
|
236 |
+
- ▁NANG
|
237 |
+
- HA
|
238 |
+
- ▁DIPUN
|
239 |
+
- ▁LE
|
240 |
+
- ▁SEKOLAH
|
241 |
+
- ▁DA
|
242 |
+
- ▁INGKANG
|
243 |
+
- ▁SENENG
|
244 |
+
- ▁KO
|
245 |
+
- ▁N
|
246 |
+
- UN
|
247 |
+
- 'NO'
|
248 |
+
- ▁MUSIK
|
249 |
+
- BI
|
250 |
+
- LAN
|
251 |
+
- ▁KUW
|
252 |
+
- ▁DE
|
253 |
+
- AR
|
254 |
+
- KI
|
255 |
+
- HAN
|
256 |
+
- ▁GA
|
257 |
+
- ▁TE
|
258 |
+
- ▁GE
|
259 |
+
- ▁BU
|
260 |
+
- ▁CA
|
261 |
+
- ▁LAGI
|
262 |
+
- ▁M
|
263 |
+
- AKÉ
|
264 |
+
- Z
|
265 |
+
- KE
|
266 |
+
- ▁MU
|
267 |
+
- ▁AS
|
268 |
+
- PI
|
269 |
+
- TH
|
270 |
+
- UR
|
271 |
+
- ▁IN
|
272 |
+
- ▁BE
|
273 |
+
- TER
|
274 |
+
- ▁TI
|
275 |
+
- ▁ALUMN
|
276 |
+
- ▁WONTEN
|
277 |
+
- DE
|
278 |
+
- SE
|
279 |
+
- CE
|
280 |
+
- DHA
|
281 |
+
- GU
|
282 |
+
- ▁AL
|
283 |
+
- ▁PI
|
284 |
+
- ▁NGRUNGOKN
|
285 |
+
- ▁RO
|
286 |
+
- MU
|
287 |
+
- ▁ORA
|
288 |
+
- PU
|
289 |
+
- ▁MO
|
290 |
+
- ▁KANGGO
|
291 |
+
- ES
|
292 |
+
- ▁NG
|
293 |
+
- ▁IS
|
294 |
+
- DO
|
295 |
+
- DU
|
296 |
+
- IS
|
297 |
+
- WE
|
298 |
+
- ▁LI
|
299 |
+
- ▁WI
|
300 |
+
- AKEN
|
301 |
+
- ▁BI
|
302 |
+
- ▁JU
|
303 |
+
- CH
|
304 |
+
- OR
|
305 |
+
- WAN
|
306 |
+
- ▁BISA
|
307 |
+
- ▁TU
|
308 |
+
- J
|
309 |
+
- NGGA
|
310 |
+
- ▁SO
|
311 |
+
- KO
|
312 |
+
- ▁G
|
313 |
+
- NDA
|
314 |
+
- ▁PAN
|
315 |
+
- UNG
|
316 |
+
- JU
|
317 |
+
- AT
|
318 |
+
- ▁MINANGKA
|
319 |
+
- W
|
320 |
+
- ▁GU
|
321 |
+
- BO
|
322 |
+
- VI
|
323 |
+
- ▁AN
|
324 |
+
- SAN
|
325 |
+
- ÈN
|
326 |
+
- ▁BO
|
327 |
+
- JI
|
328 |
+
- NIPUN
|
329 |
+
- ▁TAUN
|
330 |
+
- ▁KANTHI
|
331 |
+
- ▁TO
|
332 |
+
- ▁RI
|
333 |
+
- ▁P
|
334 |
+
- ▁SAKING
|
335 |
+
- ▁NGA
|
336 |
+
- ▁JE
|
337 |
+
- YU
|
338 |
+
- CK
|
339 |
+
- ANG
|
340 |
+
- ▁DÉNING
|
341 |
+
- ▁AR
|
342 |
+
- ▁UNIVERSITAS
|
343 |
+
- RAH
|
344 |
+
- ▁NI
|
345 |
+
- ▁MAR
|
346 |
+
- YAN
|
347 |
+
- ▁KUTHA
|
348 |
+
- ▁BANJUR
|
349 |
+
- ▁WONG
|
350 |
+
- ▁PEN
|
351 |
+
- ME
|
352 |
+
- UM
|
353 |
+
- ▁F
|
354 |
+
- ▁HA
|
355 |
+
- ST
|
356 |
+
- EM
|
357 |
+
- ▁D
|
358 |
+
- ▁UTAWA
|
359 |
+
- ▁DU
|
360 |
+
- DHU
|
361 |
+
- ▁NALIKA
|
362 |
+
- ▁THE
|
363 |
+
- GO
|
364 |
+
- AK
|
365 |
+
- UL
|
366 |
+
- LAS
|
367 |
+
- KAN
|
368 |
+
- BE
|
369 |
+
- ▁KI
|
370 |
+
- RANG
|
371 |
+
- ▁WE
|
372 |
+
- MO
|
373 |
+
- ING
|
374 |
+
- ▁PU
|
375 |
+
- ▁SIJI
|
376 |
+
- IT
|
377 |
+
- ▁PULUH
|
378 |
+
- ▁BASA
|
379 |
+
- GAN
|
380 |
+
- CI
|
381 |
+
- UT
|
382 |
+
- ▁OF
|
383 |
+
- ▁WIS
|
384 |
+
- YO
|
385 |
+
- TON
|
386 |
+
- PO
|
387 |
+
- ▁LU
|
388 |
+
- ▁NO
|
389 |
+
- ▁RU
|
390 |
+
- ▁CO
|
391 |
+
- LAH
|
392 |
+
- DHI
|
393 |
+
- ▁PRA
|
394 |
+
- ▁JO
|
395 |
+
- AH
|
396 |
+
- ▁KAR
|
397 |
+
- HO
|
398 |
+
- ÈK
|
399 |
+
- ▁PO
|
400 |
+
- ▁HI
|
401 |
+
- ET
|
402 |
+
- ▁DEWI
|
403 |
+
- ▁FA
|
404 |
+
- ANGAN
|
405 |
+
- ▁DADOS
|
406 |
+
- JO
|
407 |
+
- ▁PRO
|
408 |
+
- MBANG
|
409 |
+
- VE
|
410 |
+
- OK
|
411 |
+
- TRA
|
412 |
+
- ▁YU
|
413 |
+
- ▁MAN
|
414 |
+
- IL
|
415 |
+
- ▁PANG
|
416 |
+
- LAM
|
417 |
+
- IR
|
418 |
+
- LIS
|
419 |
+
- ▁JENENG
|
420 |
+
- VA
|
421 |
+
- ▁HO
|
422 |
+
- DRA
|
423 |
+
- WU
|
424 |
+
- TRI
|
425 |
+
- ▁INGGIH
|
426 |
+
- ▁SALAH
|
427 |
+
- ▁CE
|
428 |
+
- CO
|
429 |
+
- ▁MEN
|
430 |
+
- SON
|
431 |
+
- BAR
|
432 |
+
- ▁LO
|
433 |
+
- ▁UGI
|
434 |
+
- ▁GO
|
435 |
+
- EK
|
436 |
+
- ▁JAM
|
437 |
+
- ASI
|
438 |
+
- ▁CI
|
439 |
+
- ▁NGE
|
440 |
+
- RY
|
441 |
+
- IA
|
442 |
+
- ▁AD
|
443 |
+
- ▁NING
|
444 |
+
- ▁DHEWEKE
|
445 |
+
- NTEN
|
446 |
+
- ▁SAWIJINING
|
447 |
+
- ARA
|
448 |
+
- RIS
|
449 |
+
- TIK
|
450 |
+
- ▁PARA
|
451 |
+
- TAR
|
452 |
+
- ▁NYE
|
453 |
+
- ▁HE
|
454 |
+
- ▁V
|
455 |
+
- X
|
456 |
+
- EP
|
457 |
+
- PER
|
458 |
+
- AKE
|
459 |
+
- ▁INDONESIA
|
460 |
+
- MEN
|
461 |
+
- ▁SAN
|
462 |
+
- ▁DO
|
463 |
+
- WAR
|
464 |
+
- ▁MB
|
465 |
+
- ▁INDONÉSIA
|
466 |
+
- KAKÉ
|
467 |
+
- BER
|
468 |
+
- ▁KALIYAN
|
469 |
+
- ▁RONG
|
470 |
+
- RIA
|
471 |
+
- AM
|
472 |
+
- ▁JAWA
|
473 |
+
- ▁KAP
|
474 |
+
- ▁KAN
|
475 |
+
- ▁NU
|
476 |
+
- ▁NGANTI
|
477 |
+
- ▁ART
|
478 |
+
- ▁VI
|
479 |
+
- KAKE
|
480 |
+
- ▁FILM
|
481 |
+
- LANG
|
482 |
+
- ▁DHA
|
483 |
+
- ▁SRI
|
484 |
+
- DHO
|
485 |
+
- RENG
|
486 |
+
- ▁KAYA
|
487 |
+
- THA
|
488 |
+
- NGING
|
489 |
+
- ▁AMARG
|
490 |
+
- TUR
|
491 |
+
- DHANG
|
492 |
+
- CU
|
493 |
+
- UK
|
494 |
+
- ▁TELU
|
495 |
+
- RON
|
496 |
+
- ▁AYU
|
497 |
+
- ▁ST
|
498 |
+
- ▁NGANGGO
|
499 |
+
- ▁LUWIH
|
500 |
+
- BAT
|
501 |
+
- RING
|
502 |
+
- ▁SAMPUN
|
503 |
+
- ▁WIWIT
|
504 |
+
- TEN
|
505 |
+
- ▁GI
|
506 |
+
- RAT
|
507 |
+
- ▁KON
|
508 |
+
- LIN
|
509 |
+
- ▁AND
|
510 |
+
- NAN
|
511 |
+
- ▁NANGING
|
512 |
+
- ▁DHÈWÈKÉ
|
513 |
+
- ▁NEW
|
514 |
+
- ▁GUNUNG
|
515 |
+
- ▁Z
|
516 |
+
- SO
|
517 |
+
- ▁LORO
|
518 |
+
- ▁W
|
519 |
+
- ▁AKÈH
|
520 |
+
- ▁FO
|
521 |
+
- PAN
|
522 |
+
- ▁NDUWÈ
|
523 |
+
- KAR
|
524 |
+
- ▁HU
|
525 |
+
- ▁EWU
|
526 |
+
- ▁ATUS
|
527 |
+
- ONG
|
528 |
+
- ▁DIARANI
|
529 |
+
- ▁BEN
|
530 |
+
- ▁PALING
|
531 |
+
- ▁BAN
|
532 |
+
- IK
|
533 |
+
- NING
|
534 |
+
- ▁WERNA
|
535 |
+
- V
|
536 |
+
- OS
|
537 |
+
- GER
|
538 |
+
- ▁WOLU
|
539 |
+
- TIN
|
540 |
+
- ▁MAU
|
541 |
+
- AS
|
542 |
+
- ▁SAM
|
543 |
+
- ▁FI
|
544 |
+
- ▁KIDUL
|
545 |
+
- ▁KALI
|
546 |
+
- ▁PIYAMBAKIPUN
|
547 |
+
- ÈL
|
548 |
+
- DY
|
549 |
+
- OL
|
550 |
+
- ▁ENEM
|
551 |
+
- WÉ
|
552 |
+
- FA
|
553 |
+
- TOR
|
554 |
+
- ▁FE
|
555 |
+
- LIA
|
556 |
+
- ▁SAGED
|
557 |
+
- RUS
|
558 |
+
- TAS
|
559 |
+
- ZA
|
560 |
+
- FORD
|
561 |
+
- BAH
|
562 |
+
- MPI
|
563 |
+
- ▁ASAL
|
564 |
+
- ▁TEMBUNG
|
565 |
+
- LIK
|
566 |
+
- ▁SAIKI
|
567 |
+
- ▁PIN
|
568 |
+
- ▁JI
|
569 |
+
- ▁SHA
|
570 |
+
- BUR
|
571 |
+
- ▁KAS
|
572 |
+
- ▁SARI
|
573 |
+
- ▁WAR
|
574 |
+
- GEN
|
575 |
+
- ▁AGUS
|
576 |
+
- WO
|
577 |
+
- ▁NUR
|
578 |
+
- ▁LONDON
|
579 |
+
- ▁URIP
|
580 |
+
- MAS
|
581 |
+
- ▁PITU
|
582 |
+
- UKU
|
583 |
+
- ÈR
|
584 |
+
- WON
|
585 |
+
- DAH
|
586 |
+
- ANÉ
|
587 |
+
- ▁ND
|
588 |
+
- ▁PAM
|
589 |
+
- CARA
|
590 |
+
- ▁MARANG
|
591 |
+
- VER
|
592 |
+
- ▁HAM
|
593 |
+
- ▁LAIR
|
594 |
+
- ▁WU
|
595 |
+
- ▁ANAK
|
596 |
+
- ▁ANGG
|
597 |
+
- ▁SITI
|
598 |
+
- ▁DWI
|
599 |
+
- ARD
|
600 |
+
- DIA
|
601 |
+
- ▁KANGG
|
602 |
+
- ▁ARIF
|
603 |
+
- MER
|
604 |
+
- ▁ALI
|
605 |
+
- ▁SABEN
|
606 |
+
- MAR
|
607 |
+
- ▁CITA
|
608 |
+
- ▁BOTEN
|
609 |
+
- QI
|
610 |
+
- ▁HER
|
611 |
+
- ▁CILIK
|
612 |
+
- AD
|
613 |
+
- ▁LAJENG
|
614 |
+
- ▁PRI
|
615 |
+
- ▁INSTITUTE
|
616 |
+
- ▁IBU
|
617 |
+
- ▁LIMA
|
618 |
+
- ▁HADI
|
619 |
+
- ▁PAS
|
620 |
+
- ▁BANYU
|
621 |
+
- ▁BER
|
622 |
+
- Q
|
623 |
+
- ▁KASEBUT
|
624 |
+
- ▁ABDUL
|
625 |
+
- ▁BAMBANG
|
626 |
+
- ▁TELUNG
|
627 |
+
- WIS
|
628 |
+
- ▁KALIH
|
629 |
+
- ▁DUWÉ
|
630 |
+
- STER
|
631 |
+
- ▁ZA
|
632 |
+
- ▁DIGAWÉ
|
633 |
+
- ▁ARI
|
634 |
+
- NTUK
|
635 |
+
- ▁AWAK
|
636 |
+
- ▁AREP
|
637 |
+
- ▁NDUWÉ
|
638 |
+
- ▁NGG
|
639 |
+
- ▁ABDULLAH
|
640 |
+
- ▁TER
|
641 |
+
- ▁WULANDARI
|
642 |
+
- ▁ISIH
|
643 |
+
- ▁YO
|
644 |
+
- ▁NGU
|
645 |
+
- ▁RIF
|
646 |
+
- ▁MUNG
|
647 |
+
- RUL
|
648 |
+
- ▁PUTRA
|
649 |
+
- KON
|
650 |
+
- ▁MANGGUNG
|
651 |
+
- ▁NUG
|
652 |
+
- ▁JINIS
|
653 |
+
- SEN
|
654 |
+
- ▁AZ
|
655 |
+
- ▁JAKARTA
|
656 |
+
- MIN
|
657 |
+
- NIA
|
658 |
+
- ▁SOLO
|
659 |
+
- ▁EKO
|
660 |
+
- JAH
|
661 |
+
- TIF
|
662 |
+
- ▁DAN
|
663 |
+
- ▁SETU
|
664 |
+
- ▁BAL
|
665 |
+
- ▁AKEH
|
666 |
+
- NDER
|
667 |
+
- ▁TAU
|
668 |
+
- ▁PUJI
|
669 |
+
- ▁YOGYAKARTA
|
670 |
+
- ▁TIYANG
|
671 |
+
- ▁SARASVATI
|
672 |
+
- ▁PUN
|
673 |
+
- ▁BALI
|
674 |
+
- LAR
|
675 |
+
- NINGSIH
|
676 |
+
- ▁OR
|
677 |
+
- ENT
|
678 |
+
- ▁TENGAH
|
679 |
+
- ▁PAPAN
|
680 |
+
- ▁KIRA
|
681 |
+
- ▁JAKA
|
682 |
+
- ▁PADHA
|
683 |
+
- ▁OXFORD
|
684 |
+
- ▁MULA
|
685 |
+
- ▁EL
|
686 |
+
- ▁TUM
|
687 |
+
- ▁NGLA
|
688 |
+
- ▁SEN
|
689 |
+
- TUTI
|
690 |
+
- ROHO
|
691 |
+
- ▁SOFYAN
|
692 |
+
- ▁KABUPATÈN
|
693 |
+
- ▁WAHHAB
|
694 |
+
- ▁DHUWUR
|
695 |
+
- ▁ARUPA
|
696 |
+
- ▁MAIN
|
697 |
+
- ▁PRE
|
698 |
+
- ▁WIT
|
699 |
+
- ▁DONYA
|
700 |
+
- ▁TIM
|
701 |
+
- ▁NYA
|
702 |
+
- ▁KALEBU
|
703 |
+
- ▁PANGANAN
|
704 |
+
- ▁HAR
|
705 |
+
- FF
|
706 |
+
- ▁PRASETY
|
707 |
+
- ▁GEDHÉ
|
708 |
+
- ▁SAWISÉ
|
709 |
+
- ▁PUTRI
|
710 |
+
- TARA
|
711 |
+
- BINTANG
|
712 |
+
- LY
|
713 |
+
- ▁TEGES
|
714 |
+
- ▁BANGET
|
715 |
+
- ▁PANJENENGANIPUN
|
716 |
+
- LLY
|
717 |
+
- ▁WOH
|
718 |
+
- ▁PATANG
|
719 |
+
- ▁MISUWUR
|
720 |
+
- OLOGI
|
721 |
+
- ▁KATHAH
|
722 |
+
- DEN
|
723 |
+
- ▁CARA
|
724 |
+
- ▁OMAH
|
725 |
+
- ▁SHE
|
726 |
+
- OMB
|
727 |
+
- ▁NJ
|
728 |
+
- ▁CAMBRIDGE
|
729 |
+
- ▁BABAGAN
|
730 |
+
- MON
|
731 |
+
- ▁PAPAT
|
732 |
+
- ▁NAGARA
|
733 |
+
- ▁TEMP
|
734 |
+
- ▁SAHA
|
735 |
+
- HAM
|
736 |
+
- ▁MANGAN
|
737 |
+
- ▁SANGA
|
738 |
+
- ▁AMB
|
739 |
+
- BAN
|
740 |
+
- AGE
|
741 |
+
- ▁GODHONG
|
742 |
+
- DER
|
743 |
+
- ▁KAPING
|
744 |
+
- ▁BAKAL
|
745 |
+
- ▁LIYA
|
746 |
+
- ▁EDINBURGH
|
747 |
+
- ▁DHÉWÉ
|
748 |
+
- ÈNG
|
749 |
+
- ▁PERANG
|
750 |
+
- ▁YÈN
|
751 |
+
- ▁DUMUNUNG
|
752 |
+
- PORT
|
753 |
+
- ▁MER
|
754 |
+
- ▁PASAR
|
755 |
+
- ▁POP
|
756 |
+
- ▁PROVINSI
|
757 |
+
- ▁UMUM
|
758 |
+
- ▁US
|
759 |
+
- ▁SANGALAS
|
760 |
+
- ▁UTAMA
|
761 |
+
- ▁DIKENAL
|
762 |
+
- ▁CACAH
|
763 |
+
- LUK
|
764 |
+
- ▁WEWENGKON
|
765 |
+
- ▁GAD
|
766 |
+
- ▁INDIA
|
767 |
+
- ▁DAWA
|
768 |
+
- VO
|
769 |
+
- ▁YORK
|
770 |
+
- ▁BAB
|
771 |
+
- ▁BAHAN
|
772 |
+
- ▁JENENGÉ
|
773 |
+
- ▁KEMBANG
|
774 |
+
- ▁WETON
|
775 |
+
- ▁MENAW
|
776 |
+
- ▁MÈ
|
777 |
+
- ▁PULO
|
778 |
+
- '?'
|
779 |
+
- ▁DON
|
780 |
+
- ▁TANDURAN
|
781 |
+
- ▁KRAJAN
|
782 |
+
- ▁PITUNG
|
783 |
+
- ▁SINETRON
|
784 |
+
- ▁GRA
|
785 |
+
- ▁RAJA
|
786 |
+
- ▁JAMAN
|
787 |
+
- ▁TEN
|
788 |
+
- ▁KRA
|
789 |
+
- ▁BENTUK
|
790 |
+
- ▁SANGANG
|
791 |
+
- ▁UTAWI
|
792 |
+
- ▁WUJUD
|
793 |
+
- ▁SUKU
|
794 |
+
- ▁JOHN
|
795 |
+
- ▁KOMP
|
796 |
+
- ▁LANGKUNG
|
797 |
+
- ▁ASRING
|
798 |
+
- ▁BAPAK
|
799 |
+
- ▁HARV
|
800 |
+
- ▁INGGRIS
|
801 |
+
- ▁SISIH
|
802 |
+
- ▁DHEWEKÉ
|
803 |
+
- ▁YEN
|
804 |
+
- ▁MITURUT
|
805 |
+
- ▁TANPA
|
806 |
+
- ▁KRI
|
807 |
+
- DUR
|
808 |
+
- ▁LAGU
|
809 |
+
- ▁PUNGKASAN
|
810 |
+
- ▁LOR
|
811 |
+
- ▁ANGGOTA
|
812 |
+
- ▁PUTIH
|
813 |
+
- ▁SALIYANÉ
|
814 |
+
- ▁AZHAR
|
815 |
+
- ▁DISEBUT
|
816 |
+
- ▁KUDU
|
817 |
+
- ▁SETUNGGAL
|
818 |
+
- ▁AKSARA
|
819 |
+
- ▁BRAD
|
820 |
+
- ▁ANTARA
|
821 |
+
- NWAR
|
822 |
+
- ▁GAWÉ
|
823 |
+
- ▁MANUNGSA
|
824 |
+
- ▁GADHAH
|
825 |
+
- ▁COLLEGE
|
826 |
+
- ▁CHRIS
|
827 |
+
- ▁STAM
|
828 |
+
- ▁DAGING
|
829 |
+
- ▁KEREP
|
830 |
+
- ▁KABÈH
|
831 |
+
- UPAYA
|
832 |
+
- ▁BAGÉYAN
|
833 |
+
- ▁CHUNG
|
834 |
+
- ▁IWAK
|
835 |
+
- ▁KADOS
|
836 |
+
- ▁JEPANG
|
837 |
+
- ▁KHAS
|
838 |
+
- ▁APIK
|
839 |
+
- ▁YOU
|
840 |
+
- ▁WAYANG
|
841 |
+
- ▁WEKTU
|
842 |
+
- ▁BIYASANÉ
|
843 |
+
- ▁LIYANÉ
|
844 |
+
- ▁KULIT
|
845 |
+
- MPUNG
|
846 |
+
- ▁KULON
|
847 |
+
- ▁HIJRAH
|
848 |
+
- ▁DAVID
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decoder_conf:
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input_layer: embed
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required:
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exp/asr_train_asr_raw_bpe1000/images/acc.png
ADDED
exp/asr_train_asr_raw_bpe1000/images/backward_time.png
ADDED
exp/asr_train_asr_raw_bpe1000/images/cer.png
ADDED
exp/asr_train_asr_raw_bpe1000/images/cer_ctc.png
ADDED
exp/asr_train_asr_raw_bpe1000/images/forward_time.png
ADDED
exp/asr_train_asr_raw_bpe1000/images/iter_time.png
ADDED
exp/asr_train_asr_raw_bpe1000/images/loss.png
ADDED
exp/asr_train_asr_raw_bpe1000/images/loss_att.png
ADDED
exp/asr_train_asr_raw_bpe1000/images/loss_ctc.png
ADDED
exp/asr_train_asr_raw_bpe1000/images/lr_0.png
ADDED
exp/asr_train_asr_raw_bpe1000/images/optim_step_time.png
ADDED
exp/asr_train_asr_raw_bpe1000/images/train_time.png
ADDED
exp/asr_train_asr_raw_bpe1000/images/wer.png
ADDED
exp/asr_train_asr_raw_bpe1000/valid.acc.best.pth
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 111676310
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meta.yaml
ADDED
@@ -0,0 +1,8 @@
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1 |
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espnet: 0.10.0
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2 |
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files:
|
3 |
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asr_model_file: exp/asr_train_asr_raw_bpe1000/valid.acc.best.pth
|
4 |
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python: "3.8.5 (default, Sep 4 2020, 07:30:14) \n[GCC 7.3.0]"
|
5 |
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timestamp: 1625878616.133883
|
6 |
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torch: 1.8.1+cu102
|
7 |
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yaml_files:
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8 |
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asr_train_config: exp/asr_train_asr_raw_bpe1000/config.yaml
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