Update model
Browse files- README.md +304 -0
- meta.yaml +8 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/29epoch.pth +3 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/RESULTS.md +17 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/config.yaml +213 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/backward_time.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/clip.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/eer.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/forward_time.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/gpu_max_cached_mem_GB.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/grad_norm.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/iter_time.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/loss.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/loss_scale.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/mindcf.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/n_trials.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/nontrg_mean.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/nontrg_std.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/optim0_lr0.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/optim_step_time.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/train_time.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/trg_mean.png +0 -0
- save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/trg_std.png +0 -0
README.md
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1 |
+
---
|
2 |
+
tags:
|
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+
- espnet
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4 |
+
- audio
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5 |
+
- speaker-recognition
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6 |
+
language: multilingual
|
7 |
+
datasets:
|
8 |
+
- voxceleb
|
9 |
+
license: cc-by-4.0
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10 |
+
---
|
11 |
+
|
12 |
+
## ESPnet2 SPK model
|
13 |
+
|
14 |
+
### `espnet/voxcelebs12_mfaconformer_mel`
|
15 |
+
|
16 |
+
This model was trained by Jungjee using voxceleb recipe in [espnet](https://github.com/espnet/espnet/).
|
17 |
+
|
18 |
+
### Demo: How to use in ESPnet2
|
19 |
+
|
20 |
+
Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html)
|
21 |
+
if you haven't done that already.
|
22 |
+
|
23 |
+
```bash
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24 |
+
cd espnet
|
25 |
+
git checkout ea74d1c7482bf5b3b4f90410d1ca8521fd9a566b
|
26 |
+
pip install -e .
|
27 |
+
cd egs2/voxceleb/spk1
|
28 |
+
./run.sh --skip_data_prep false --skip_train true --download_model espnet/voxcelebs12_mfaconformer_mel
|
29 |
+
```
|
30 |
+
|
31 |
+
<!-- Generated by scripts/utils/show_spk_result.py -->
|
32 |
+
# RESULTS
|
33 |
+
## Environments
|
34 |
+
date: 2023-11-30 15:48:13.707576
|
35 |
+
|
36 |
+
- python version: 3.9.16 (main, May 15 2023, 23:46:34) [GCC 11.2.0]
|
37 |
+
- espnet version: 202310
|
38 |
+
- pytorch version: 1.13.1
|
39 |
+
|
40 |
+
| | Mean | Std |
|
41 |
+
|---|---|---|
|
42 |
+
| Target | -0.8149 | 0.1386 |
|
43 |
+
| Non-target | 0.0828 | 0.0828 |
|
44 |
+
|
45 |
+
| Model name | EER(%) | minDCF |
|
46 |
+
|---|---|---|
|
47 |
+
| mfa-conformer | 0.952 | 0.05834 |
|
48 |
+
|
49 |
+
## SPK config
|
50 |
+
|
51 |
+
<details><summary>expand</summary>
|
52 |
+
|
53 |
+
```
|
54 |
+
config: conf/tuning/train_mfa_conformer_adamw.yaml
|
55 |
+
print_config: false
|
56 |
+
log_level: INFO
|
57 |
+
drop_last_iter: true
|
58 |
+
dry_run: false
|
59 |
+
iterator_type: category
|
60 |
+
valid_iterator_type: sequence
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61 |
+
output_dir: exp/spk_train_mfa_conformer_adamw_raw_sp
|
62 |
+
ngpu: 1
|
63 |
+
seed: 0
|
64 |
+
num_workers: 6
|
65 |
+
num_att_plot: 0
|
66 |
+
dist_backend: nccl
|
67 |
+
dist_init_method: env://
|
68 |
+
dist_world_size: 4
|
69 |
+
dist_rank: 0
|
70 |
+
local_rank: 0
|
71 |
+
dist_master_addr: localhost
|
72 |
+
dist_master_port: 46597
|
73 |
+
dist_launcher: null
|
74 |
+
multiprocessing_distributed: true
|
75 |
+
unused_parameters: false
|
76 |
+
sharded_ddp: false
|
77 |
+
cudnn_enabled: true
|
78 |
+
cudnn_benchmark: true
|
79 |
+
cudnn_deterministic: false
|
80 |
+
collect_stats: false
|
81 |
+
write_collected_feats: false
|
82 |
+
max_epoch: 40
|
83 |
+
patience: null
|
84 |
+
val_scheduler_criterion:
|
85 |
+
- valid
|
86 |
+
- loss
|
87 |
+
early_stopping_criterion:
|
88 |
+
- valid
|
89 |
+
- loss
|
90 |
+
- min
|
91 |
+
best_model_criterion:
|
92 |
+
- - valid
|
93 |
+
- eer
|
94 |
+
- min
|
95 |
+
keep_nbest_models: 3
|
96 |
+
nbest_averaging_interval: 0
|
97 |
+
grad_clip: 9999
|
98 |
+
grad_clip_type: 2.0
|
99 |
+
grad_noise: false
|
100 |
+
accum_grad: 1
|
101 |
+
no_forward_run: false
|
102 |
+
resume: true
|
103 |
+
train_dtype: float32
|
104 |
+
use_amp: false
|
105 |
+
log_interval: 100
|
106 |
+
use_matplotlib: true
|
107 |
+
use_tensorboard: true
|
108 |
+
create_graph_in_tensorboard: false
|
109 |
+
use_wandb: false
|
110 |
+
wandb_project: null
|
111 |
+
wandb_id: null
|
112 |
+
wandb_entity: null
|
113 |
+
wandb_name: null
|
114 |
+
wandb_model_log_interval: -1
|
115 |
+
detect_anomaly: false
|
116 |
+
use_lora: false
|
117 |
+
save_lora_only: true
|
118 |
+
lora_conf: {}
|
119 |
+
pretrain_path: null
|
120 |
+
init_param: []
|
121 |
+
ignore_init_mismatch: false
|
122 |
+
freeze_param: []
|
123 |
+
num_iters_per_epoch: null
|
124 |
+
batch_size: 512
|
125 |
+
valid_batch_size: 40
|
126 |
+
batch_bins: 1000000
|
127 |
+
valid_batch_bins: null
|
128 |
+
train_shape_file:
|
129 |
+
- exp/spk_stats_16k_sp/train/speech_shape
|
130 |
+
valid_shape_file:
|
131 |
+
- exp/spk_stats_16k_sp/valid/speech_shape
|
132 |
+
batch_type: folded
|
133 |
+
valid_batch_type: null
|
134 |
+
fold_length:
|
135 |
+
- 120000
|
136 |
+
sort_in_batch: descending
|
137 |
+
shuffle_within_batch: false
|
138 |
+
sort_batch: descending
|
139 |
+
multiple_iterator: false
|
140 |
+
chunk_length: 500
|
141 |
+
chunk_shift_ratio: 0.5
|
142 |
+
num_cache_chunks: 1024
|
143 |
+
chunk_excluded_key_prefixes: []
|
144 |
+
chunk_default_fs: null
|
145 |
+
train_data_path_and_name_and_type:
|
146 |
+
- - dump/raw/voxceleb12_devs_sp/wav.scp
|
147 |
+
- speech
|
148 |
+
- sound
|
149 |
+
- - dump/raw/voxceleb12_devs_sp/utt2spk
|
150 |
+
- spk_labels
|
151 |
+
- text
|
152 |
+
valid_data_path_and_name_and_type:
|
153 |
+
- - dump/raw/voxceleb1_test/trial.scp
|
154 |
+
- speech
|
155 |
+
- sound
|
156 |
+
- - dump/raw/voxceleb1_test/trial2.scp
|
157 |
+
- speech2
|
158 |
+
- sound
|
159 |
+
- - dump/raw/voxceleb1_test/trial_label
|
160 |
+
- spk_labels
|
161 |
+
- text
|
162 |
+
allow_variable_data_keys: false
|
163 |
+
max_cache_size: 0.0
|
164 |
+
max_cache_fd: 32
|
165 |
+
allow_multi_rates: false
|
166 |
+
valid_max_cache_size: null
|
167 |
+
exclude_weight_decay: false
|
168 |
+
exclude_weight_decay_conf: {}
|
169 |
+
optim: adamw
|
170 |
+
optim_conf:
|
171 |
+
lr: 0.001
|
172 |
+
weight_decay: 1.0e-07
|
173 |
+
amsgrad: false
|
174 |
+
scheduler: cosineannealingwarmuprestarts
|
175 |
+
scheduler_conf:
|
176 |
+
first_cycle_steps: 250000
|
177 |
+
cycle_mult: 1.0
|
178 |
+
max_lr: 0.001
|
179 |
+
min_lr: 1.0e-08
|
180 |
+
warmup_steps: 10000
|
181 |
+
gamma: 0.7
|
182 |
+
init: null
|
183 |
+
use_preprocessor: true
|
184 |
+
input_size: null
|
185 |
+
target_duration: 3.0
|
186 |
+
spk2utt: dump/raw/voxceleb12_devs_sp/spk2utt
|
187 |
+
spk_num: 21615
|
188 |
+
sample_rate: 16000
|
189 |
+
num_eval: 10
|
190 |
+
rir_scp: ''
|
191 |
+
model_conf:
|
192 |
+
extract_feats_in_collect_stats: false
|
193 |
+
frontend: melspec_torch
|
194 |
+
frontend_conf:
|
195 |
+
preemp: true
|
196 |
+
n_fft: 512
|
197 |
+
log: true
|
198 |
+
win_length: 400
|
199 |
+
hop_length: 160
|
200 |
+
n_mels: 80
|
201 |
+
normalize: mn
|
202 |
+
specaug: null
|
203 |
+
specaug_conf: {}
|
204 |
+
normalize: null
|
205 |
+
normalize_conf: {}
|
206 |
+
encoder: mfaconformer
|
207 |
+
encoder_conf:
|
208 |
+
output_size: 512
|
209 |
+
attention_heads: 8
|
210 |
+
linear_units: 2048
|
211 |
+
num_blocks: 6
|
212 |
+
dropout_rate: 0.1
|
213 |
+
positional_dropout_rate: 0.1
|
214 |
+
attention_dropout_rate: 0.1
|
215 |
+
input_layer: conv2d2
|
216 |
+
normalize_before: true
|
217 |
+
macaron_style: true
|
218 |
+
rel_pos_type: latest
|
219 |
+
pos_enc_layer_type: rel_pos
|
220 |
+
selfattention_layer_type: rel_selfattn
|
221 |
+
activation_type: swish
|
222 |
+
use_cnn_module: true
|
223 |
+
cnn_module_kernel: 15
|
224 |
+
pooling: chn_attn_stat
|
225 |
+
pooling_conf: {}
|
226 |
+
projector: rawnet3
|
227 |
+
projector_conf:
|
228 |
+
output_size: 192
|
229 |
+
preprocessor: spk
|
230 |
+
preprocessor_conf:
|
231 |
+
target_duration: 3.0
|
232 |
+
sample_rate: 16000
|
233 |
+
num_eval: 5
|
234 |
+
noise_apply_prob: 0.5
|
235 |
+
noise_info:
|
236 |
+
- - 1.0
|
237 |
+
- dump/raw/musan_speech.scp
|
238 |
+
- - 4
|
239 |
+
- 7
|
240 |
+
- - 13
|
241 |
+
- 20
|
242 |
+
- - 1.0
|
243 |
+
- dump/raw/musan_noise.scp
|
244 |
+
- - 1
|
245 |
+
- 1
|
246 |
+
- - 0
|
247 |
+
- 15
|
248 |
+
- - 1.0
|
249 |
+
- dump/raw/musan_music.scp
|
250 |
+
- - 1
|
251 |
+
- 1
|
252 |
+
- - 5
|
253 |
+
- 15
|
254 |
+
rir_apply_prob: 0.5
|
255 |
+
rir_scp: dump/raw/rirs.scp
|
256 |
+
loss: aamsoftmax_sc_topk
|
257 |
+
loss_conf:
|
258 |
+
margin: 0.3
|
259 |
+
scale: 30
|
260 |
+
K: 3
|
261 |
+
mp: 0.06
|
262 |
+
k_top: 5
|
263 |
+
required:
|
264 |
+
- output_dir
|
265 |
+
version: '202310'
|
266 |
+
distributed: true
|
267 |
+
```
|
268 |
+
|
269 |
+
</details>
|
270 |
+
|
271 |
+
|
272 |
+
|
273 |
+
### Citing ESPnet
|
274 |
+
|
275 |
+
```BibTex
|
276 |
+
@inproceedings{watanabe2018espnet,
|
277 |
+
author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
|
278 |
+
title={{ESPnet}: End-to-End Speech Processing Toolkit},
|
279 |
+
year={2018},
|
280 |
+
booktitle={Proceedings of Interspeech},
|
281 |
+
pages={2207--2211},
|
282 |
+
doi={10.21437/Interspeech.2018-1456},
|
283 |
+
url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
|
284 |
+
}
|
285 |
+
|
286 |
+
|
287 |
+
|
288 |
+
|
289 |
+
|
290 |
+
|
291 |
+
```
|
292 |
+
|
293 |
+
or arXiv:
|
294 |
+
|
295 |
+
```bibtex
|
296 |
+
@misc{watanabe2018espnet,
|
297 |
+
title={ESPnet: End-to-End Speech Processing Toolkit},
|
298 |
+
author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
|
299 |
+
year={2018},
|
300 |
+
eprint={1804.00015},
|
301 |
+
archivePrefix={arXiv},
|
302 |
+
primaryClass={cs.CL}
|
303 |
+
}
|
304 |
+
```
|
meta.yaml
ADDED
@@ -0,0 +1,8 @@
|
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|
1 |
+
espnet: '202310'
|
2 |
+
files:
|
3 |
+
model_file: save_exp/spk_train_mfa_conformer_adamw_raw_sp/29epoch.pth
|
4 |
+
python: "3.9.16 (main, Mar 8 2023, 14:00:05) \n[GCC 11.2.0]"
|
5 |
+
timestamp: 1704235958.32165
|
6 |
+
torch: 2.0.1
|
7 |
+
yaml_files:
|
8 |
+
train_config: save_exp/spk_train_mfa_conformer_adamw_raw_sp/config.yaml
|
save_exp/spk_train_mfa_conformer_adamw_raw_sp/29epoch.pth
ADDED
@@ -0,0 +1,3 @@
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|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:416a6867ef6ad4a42cb2edd1bc95377ef87e622800dcb8617c72426835be69e8
|
3 |
+
size 260989417
|
save_exp/spk_train_mfa_conformer_adamw_raw_sp/RESULTS.md
ADDED
@@ -0,0 +1,17 @@
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|
1 |
+
<!-- Generated by scripts/utils/show_spk_result.py -->
|
2 |
+
# RESULTS
|
3 |
+
## Environments
|
4 |
+
date: 2023-11-30 15:48:13.707576
|
5 |
+
|
6 |
+
- python version: 3.9.16 (main, May 15 2023, 23:46:34) [GCC 11.2.0]
|
7 |
+
- espnet version: 202310
|
8 |
+
- pytorch version: 1.13.1
|
9 |
+
|
10 |
+
| | Mean | Std |
|
11 |
+
|---|---|---|
|
12 |
+
| Target | -0.8149 | 0.1386 |
|
13 |
+
| Non-target | 0.0828 | 0.0828 |
|
14 |
+
|
15 |
+
| Model name | EER(%) | minDCF |
|
16 |
+
|---|---|---|
|
17 |
+
| mfa-conformer | 0.952 | 0.05834 |
|
save_exp/spk_train_mfa_conformer_adamw_raw_sp/config.yaml
ADDED
@@ -0,0 +1,213 @@
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|
|
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|
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|
|
|
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|
|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
config: conf/tuning/train_mfa_conformer_adamw.yaml
|
2 |
+
print_config: false
|
3 |
+
log_level: INFO
|
4 |
+
drop_last_iter: true
|
5 |
+
dry_run: false
|
6 |
+
iterator_type: category
|
7 |
+
valid_iterator_type: sequence
|
8 |
+
output_dir: exp/spk_train_mfa_conformer_adamw_raw_sp
|
9 |
+
ngpu: 1
|
10 |
+
seed: 0
|
11 |
+
num_workers: 6
|
12 |
+
num_att_plot: 0
|
13 |
+
dist_backend: nccl
|
14 |
+
dist_init_method: env://
|
15 |
+
dist_world_size: 4
|
16 |
+
dist_rank: 0
|
17 |
+
local_rank: 0
|
18 |
+
dist_master_addr: localhost
|
19 |
+
dist_master_port: 46597
|
20 |
+
dist_launcher: null
|
21 |
+
multiprocessing_distributed: true
|
22 |
+
unused_parameters: false
|
23 |
+
sharded_ddp: false
|
24 |
+
cudnn_enabled: true
|
25 |
+
cudnn_benchmark: true
|
26 |
+
cudnn_deterministic: false
|
27 |
+
collect_stats: false
|
28 |
+
write_collected_feats: false
|
29 |
+
max_epoch: 40
|
30 |
+
patience: null
|
31 |
+
val_scheduler_criterion:
|
32 |
+
- valid
|
33 |
+
- loss
|
34 |
+
early_stopping_criterion:
|
35 |
+
- valid
|
36 |
+
- loss
|
37 |
+
- min
|
38 |
+
best_model_criterion:
|
39 |
+
- - valid
|
40 |
+
- eer
|
41 |
+
- min
|
42 |
+
keep_nbest_models: 3
|
43 |
+
nbest_averaging_interval: 0
|
44 |
+
grad_clip: 9999
|
45 |
+
grad_clip_type: 2.0
|
46 |
+
grad_noise: false
|
47 |
+
accum_grad: 1
|
48 |
+
no_forward_run: false
|
49 |
+
resume: true
|
50 |
+
train_dtype: float32
|
51 |
+
use_amp: false
|
52 |
+
log_interval: 100
|
53 |
+
use_matplotlib: true
|
54 |
+
use_tensorboard: true
|
55 |
+
create_graph_in_tensorboard: false
|
56 |
+
use_wandb: false
|
57 |
+
wandb_project: null
|
58 |
+
wandb_id: null
|
59 |
+
wandb_entity: null
|
60 |
+
wandb_name: null
|
61 |
+
wandb_model_log_interval: -1
|
62 |
+
detect_anomaly: false
|
63 |
+
use_lora: false
|
64 |
+
save_lora_only: true
|
65 |
+
lora_conf: {}
|
66 |
+
pretrain_path: null
|
67 |
+
init_param: []
|
68 |
+
ignore_init_mismatch: false
|
69 |
+
freeze_param: []
|
70 |
+
num_iters_per_epoch: null
|
71 |
+
batch_size: 512
|
72 |
+
valid_batch_size: 40
|
73 |
+
batch_bins: 1000000
|
74 |
+
valid_batch_bins: null
|
75 |
+
train_shape_file:
|
76 |
+
- exp/spk_stats_16k_sp/train/speech_shape
|
77 |
+
valid_shape_file:
|
78 |
+
- exp/spk_stats_16k_sp/valid/speech_shape
|
79 |
+
batch_type: folded
|
80 |
+
valid_batch_type: null
|
81 |
+
fold_length:
|
82 |
+
- 120000
|
83 |
+
sort_in_batch: descending
|
84 |
+
shuffle_within_batch: false
|
85 |
+
sort_batch: descending
|
86 |
+
multiple_iterator: false
|
87 |
+
chunk_length: 500
|
88 |
+
chunk_shift_ratio: 0.5
|
89 |
+
num_cache_chunks: 1024
|
90 |
+
chunk_excluded_key_prefixes: []
|
91 |
+
chunk_default_fs: null
|
92 |
+
train_data_path_and_name_and_type:
|
93 |
+
- - dump/raw/voxceleb12_devs_sp/wav.scp
|
94 |
+
- speech
|
95 |
+
- sound
|
96 |
+
- - dump/raw/voxceleb12_devs_sp/utt2spk
|
97 |
+
- spk_labels
|
98 |
+
- text
|
99 |
+
valid_data_path_and_name_and_type:
|
100 |
+
- - dump/raw/voxceleb1_test/trial.scp
|
101 |
+
- speech
|
102 |
+
- sound
|
103 |
+
- - dump/raw/voxceleb1_test/trial2.scp
|
104 |
+
- speech2
|
105 |
+
- sound
|
106 |
+
- - dump/raw/voxceleb1_test/trial_label
|
107 |
+
- spk_labels
|
108 |
+
- text
|
109 |
+
allow_variable_data_keys: false
|
110 |
+
max_cache_size: 0.0
|
111 |
+
max_cache_fd: 32
|
112 |
+
allow_multi_rates: false
|
113 |
+
valid_max_cache_size: null
|
114 |
+
exclude_weight_decay: false
|
115 |
+
exclude_weight_decay_conf: {}
|
116 |
+
optim: adamw
|
117 |
+
optim_conf:
|
118 |
+
lr: 0.001
|
119 |
+
weight_decay: 1.0e-07
|
120 |
+
amsgrad: false
|
121 |
+
scheduler: cosineannealingwarmuprestarts
|
122 |
+
scheduler_conf:
|
123 |
+
first_cycle_steps: 250000
|
124 |
+
cycle_mult: 1.0
|
125 |
+
max_lr: 0.001
|
126 |
+
min_lr: 1.0e-08
|
127 |
+
warmup_steps: 10000
|
128 |
+
gamma: 0.7
|
129 |
+
init: null
|
130 |
+
use_preprocessor: true
|
131 |
+
input_size: null
|
132 |
+
target_duration: 3.0
|
133 |
+
spk2utt: dump/raw/voxceleb12_devs_sp/spk2utt
|
134 |
+
spk_num: 21615
|
135 |
+
sample_rate: 16000
|
136 |
+
num_eval: 10
|
137 |
+
rir_scp: ''
|
138 |
+
model_conf:
|
139 |
+
extract_feats_in_collect_stats: false
|
140 |
+
frontend: melspec_torch
|
141 |
+
frontend_conf:
|
142 |
+
preemp: true
|
143 |
+
n_fft: 512
|
144 |
+
log: true
|
145 |
+
win_length: 400
|
146 |
+
hop_length: 160
|
147 |
+
n_mels: 80
|
148 |
+
normalize: mn
|
149 |
+
specaug: null
|
150 |
+
specaug_conf: {}
|
151 |
+
normalize: null
|
152 |
+
normalize_conf: {}
|
153 |
+
encoder: mfaconformer
|
154 |
+
encoder_conf:
|
155 |
+
output_size: 512
|
156 |
+
attention_heads: 8
|
157 |
+
linear_units: 2048
|
158 |
+
num_blocks: 6
|
159 |
+
dropout_rate: 0.1
|
160 |
+
positional_dropout_rate: 0.1
|
161 |
+
attention_dropout_rate: 0.1
|
162 |
+
input_layer: conv2d2
|
163 |
+
normalize_before: true
|
164 |
+
macaron_style: true
|
165 |
+
rel_pos_type: latest
|
166 |
+
pos_enc_layer_type: rel_pos
|
167 |
+
selfattention_layer_type: rel_selfattn
|
168 |
+
activation_type: swish
|
169 |
+
use_cnn_module: true
|
170 |
+
cnn_module_kernel: 15
|
171 |
+
pooling: chn_attn_stat
|
172 |
+
pooling_conf: {}
|
173 |
+
projector: rawnet3
|
174 |
+
projector_conf:
|
175 |
+
output_size: 192
|
176 |
+
preprocessor: spk
|
177 |
+
preprocessor_conf:
|
178 |
+
target_duration: 3.0
|
179 |
+
sample_rate: 16000
|
180 |
+
num_eval: 5
|
181 |
+
noise_apply_prob: 0.5
|
182 |
+
noise_info:
|
183 |
+
- - 1.0
|
184 |
+
- dump/raw/musan_speech.scp
|
185 |
+
- - 4
|
186 |
+
- 7
|
187 |
+
- - 13
|
188 |
+
- 20
|
189 |
+
- - 1.0
|
190 |
+
- dump/raw/musan_noise.scp
|
191 |
+
- - 1
|
192 |
+
- 1
|
193 |
+
- - 0
|
194 |
+
- 15
|
195 |
+
- - 1.0
|
196 |
+
- dump/raw/musan_music.scp
|
197 |
+
- - 1
|
198 |
+
- 1
|
199 |
+
- - 5
|
200 |
+
- 15
|
201 |
+
rir_apply_prob: 0.5
|
202 |
+
rir_scp: dump/raw/rirs.scp
|
203 |
+
loss: aamsoftmax_sc_topk
|
204 |
+
loss_conf:
|
205 |
+
margin: 0.3
|
206 |
+
scale: 30
|
207 |
+
K: 3
|
208 |
+
mp: 0.06
|
209 |
+
k_top: 5
|
210 |
+
required:
|
211 |
+
- output_dir
|
212 |
+
version: '202310'
|
213 |
+
distributed: true
|
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/backward_time.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/clip.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/eer.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/forward_time.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/gpu_max_cached_mem_GB.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/grad_norm.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/iter_time.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/loss.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/loss_scale.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/mindcf.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/n_trials.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/nontrg_mean.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/nontrg_std.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/optim0_lr0.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/optim_step_time.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/train_time.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/trg_mean.png
ADDED
save_exp/spk_train_mfa_conformer_adamw_raw_sp/images/trg_std.png
ADDED