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嘉渊 2023-05-11 15:05:57 +08:00
parent cf3644f96c
commit 280593676b
3 changed files with 21 additions and 169 deletions
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80
egs/librispeech/conformer/conf/train_asr_conformer_uttnorm.yaml
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@ -1,80 +0,0 @@
encoder: conformer
encoder_conf:
output_size: 512
attention_heads: 8
linear_units: 2048
num_blocks: 12
dropout_rate: 0.1
positional_dropout_rate: 0.1
attention_dropout_rate: 0.1
input_layer: conv2d
normalize_before: true
macaron_style: true
rel_pos_type: latest
pos_enc_layer_type: rel_pos
selfattention_layer_type: rel_selfattn
activation_type: swish
use_cnn_module: true
cnn_module_kernel: 31
decoder: transformer
decoder_conf:
attention_heads: 8
linear_units: 2048
num_blocks: 6
dropout_rate: 0.1
positional_dropout_rate: 0.1
self_attention_dropout_rate: 0.1
src_attention_dropout_rate: 0.1
model_conf:
ctc_weight: 0.3
lsm_weight: 0.1
length_normalized_loss: false
accum_grad: 2
max_epoch: 50
patience: none
init: none
best_model_criterion:
- - valid
- acc
- max
keep_nbest_models: 10
optim: adam
optim_conf:
lr: 0.0025
weight_decay: 0.000001
scheduler: warmuplr
scheduler_conf:
warmup_steps: 40000
specaug: specaug
specaug_conf:
apply_time_warp: true
time_warp_window: 5
time_warp_mode: bicubic
apply_freq_mask: true
freq_mask_width_range:
- 0
- 27
num_freq_mask: 2
apply_time_mask: true
time_mask_width_ratio_range:
- 0.
- 0.05
num_time_mask: 10
dataset_conf:
shuffle: True
shuffle_conf:
shuffle_size: 1024
sort_size: 500
batch_conf:
batch_type: token
batch_size: 10000
num_workers: 8
log_interval: 50
normalize: utterance_mvn

30
egs/librispeech_100h/conformer/conf/train_asr_conformer.yaml
View File

@ -1,8 +1,8 @@
encoder: conformer
encoder_conf:
output_size: 512
attention_heads: 8
linear_units: 2048
output_size: 256
attention_heads: 4
linear_units: 1024
num_blocks: 12
dropout_rate: 0.1
positional_dropout_rate: 0.1
@ -19,7 +19,7 @@ encoder_conf:
decoder: transformer
decoder_conf:
attention_heads: 8
attention_heads: 4
linear_units: 2048
num_blocks: 6
dropout_rate: 0.1
@ -27,13 +27,25 @@ decoder_conf:
self_attention_dropout_rate: 0.1
src_attention_dropout_rate: 0.1
# frontend related
frontend: wav_frontend
frontend_conf:
fs: 16000
window: hamming
n_mels: 80
frame_length: 25
frame_shift: 10
lfr_m: 1
lfr_n: 1
# hybrid CTC/attention
model_conf:
ctc_weight: 0.3
lsm_weight: 0.1
length_normalized_loss: false
accum_grad: 2
max_epoch: 50
accum_grad: 1
max_epoch: 210
patience: none
init: none
best_model_criterion:
@ -44,11 +56,11 @@ keep_nbest_models: 10
optim: adam
optim_conf:
lr: 0.0025
lr: 0.002
weight_decay: 0.000001
scheduler: warmuplr
scheduler_conf:
warmup_steps: 40000
warmup_steps: 15000
specaug: specaug
specaug_conf:
@ -64,7 +76,7 @@ specaug_conf:
time_mask_width_ratio_range:
- 0.
- 0.05
num_time_mask: 10
num_time_mask: 5
dataset_conf:
shuffle: True

80
egs/librispeech_100h/conformer/conf/train_asr_conformer_uttnorm.yaml
View File

@ -1,80 +0,0 @@
encoder: conformer
encoder_conf:
output_size: 512
attention_heads: 8
linear_units: 2048
num_blocks: 12
dropout_rate: 0.1
positional_dropout_rate: 0.1
attention_dropout_rate: 0.1
input_layer: conv2d
normalize_before: true
macaron_style: true
rel_pos_type: latest
pos_enc_layer_type: rel_pos
selfattention_layer_type: rel_selfattn
activation_type: swish
use_cnn_module: true
cnn_module_kernel: 31
decoder: transformer
decoder_conf:
attention_heads: 8
linear_units: 2048
num_blocks: 6
dropout_rate: 0.1
positional_dropout_rate: 0.1
self_attention_dropout_rate: 0.1
src_attention_dropout_rate: 0.1
model_conf:
ctc_weight: 0.3
lsm_weight: 0.1
length_normalized_loss: false
accum_grad: 2
max_epoch: 50
patience: none
init: none
best_model_criterion:
- - valid
- acc
- max
keep_nbest_models: 10
optim: adam
optim_conf:
lr: 0.0025
weight_decay: 0.000001
scheduler: warmuplr
scheduler_conf:
warmup_steps: 40000
specaug: specaug
specaug_conf:
apply_time_warp: true
time_warp_window: 5
time_warp_mode: bicubic
apply_freq_mask: true
freq_mask_width_range:
- 0
- 27
num_freq_mask: 2
apply_time_mask: true
time_mask_width_ratio_range:
- 0.
- 0.05
num_time_mask: 10
dataset_conf:
shuffle: True
shuffle_conf:
shuffle_size: 1024
sort_size: 500
batch_conf:
batch_type: token
batch_size: 10000
num_workers: 8
log_interval: 50
normalize: utterance_mvn