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嘉渊 2023-07-13 11:08:58 +08:00
parent c5127a1a5d
commit 128caa57c2
7 changed files with 3 additions and 420 deletions
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2
egs/aishell/branchformer/conf/train_asr_branchformer.yaml
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@ -97,7 +97,7 @@ dataset_conf:
sort_size: 500
batch_conf:
batch_type: token
batch_size: 20000
batch_size: 10000
num_workers: 8
log_interval: 50

104
egs/aishell/branchformer/conf/train_asr_branchformer_bs10000.yaml
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@ -1,104 +0,0 @@
# network architecture
# encoder related
encoder: branchformer
encoder_conf:
output_size: 256
use_attn: true
attention_heads: 4
attention_layer_type: rel_selfattn
pos_enc_layer_type: rel_pos
rel_pos_type: latest
use_cgmlp: true
cgmlp_linear_units: 2048
cgmlp_conv_kernel: 31
use_linear_after_conv: false
gate_activation: identity
merge_method: concat
cgmlp_weight: 0.5 # used only if merge_method is "fixed_ave"
attn_branch_drop_rate: 0.0 # used only if merge_method is "learned_ave"
num_blocks: 24
dropout_rate: 0.1
positional_dropout_rate: 0.1
attention_dropout_rate: 0.1
input_layer: conv2d
stochastic_depth_rate: 0.0
# decoder related
decoder: transformer
decoder_conf:
attention_heads: 4
linear_units: 2048
num_blocks: 6
dropout_rate: 0.1
positional_dropout_rate: 0.1
self_attention_dropout_rate: 0.
src_attention_dropout_rate: 0.
# 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 # label smoothing option
length_normalized_loss: false
# optimization related
accum_grad: 1
grad_clip: 5
max_epoch: 180
val_scheduler_criterion:
- valid
- acc
best_model_criterion:
- - valid
- acc
- max
keep_nbest_models: 10
optim: adam
optim_conf:
lr: 0.001
weight_decay: 0.000001
scheduler: warmuplr
scheduler_conf:
warmup_steps: 35000
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:
data_names: speech,text
data_types: sound,text
shuffle: True
shuffle_conf:
shuffle_size: 2048
sort_size: 500
batch_conf:
batch_type: token
batch_size: 10000
num_workers: 8
log_interval: 50
normalize: None

104
egs/aishell/branchformer/conf/train_asr_branchformer_bs16000.yaml
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@ -1,104 +0,0 @@
# network architecture
# encoder related
encoder: branchformer
encoder_conf:
output_size: 256
use_attn: true
attention_heads: 4
attention_layer_type: rel_selfattn
pos_enc_layer_type: rel_pos
rel_pos_type: latest
use_cgmlp: true
cgmlp_linear_units: 2048
cgmlp_conv_kernel: 31
use_linear_after_conv: false
gate_activation: identity
merge_method: concat
cgmlp_weight: 0.5 # used only if merge_method is "fixed_ave"
attn_branch_drop_rate: 0.0 # used only if merge_method is "learned_ave"
num_blocks: 24
dropout_rate: 0.1
positional_dropout_rate: 0.1
attention_dropout_rate: 0.1
input_layer: conv2d
stochastic_depth_rate: 0.0
# decoder related
decoder: transformer
decoder_conf:
attention_heads: 4
linear_units: 2048
num_blocks: 6
dropout_rate: 0.1
positional_dropout_rate: 0.1
self_attention_dropout_rate: 0.
src_attention_dropout_rate: 0.
# 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 # label smoothing option
length_normalized_loss: false
# optimization related
accum_grad: 1
grad_clip: 5
max_epoch: 180
val_scheduler_criterion:
- valid
- acc
best_model_criterion:
- - valid
- acc
- max
keep_nbest_models: 10
optim: adam
optim_conf:
lr: 0.001
weight_decay: 0.000001
scheduler: warmuplr
scheduler_conf:
warmup_steps: 35000
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:
data_names: speech,text
data_types: sound,text
shuffle: True
shuffle_conf:
shuffle_size: 2048
sort_size: 500
batch_conf:
batch_type: token
batch_size: 16000
num_workers: 8
log_interval: 50
normalize: None

104
egs/aishell/branchformer/conf/train_asr_branchformer_bs16000_gc2.yaml
View File

@ -1,104 +0,0 @@
# network architecture
# encoder related
encoder: branchformer
encoder_conf:
output_size: 256
use_attn: true
attention_heads: 4
attention_layer_type: rel_selfattn
pos_enc_layer_type: rel_pos
rel_pos_type: latest
use_cgmlp: true
cgmlp_linear_units: 2048
cgmlp_conv_kernel: 31
use_linear_after_conv: false
gate_activation: identity
merge_method: concat
cgmlp_weight: 0.5 # used only if merge_method is "fixed_ave"
attn_branch_drop_rate: 0.0 # used only if merge_method is "learned_ave"
num_blocks: 24
dropout_rate: 0.1
positional_dropout_rate: 0.1
attention_dropout_rate: 0.1
input_layer: conv2d
stochastic_depth_rate: 0.0
# decoder related
decoder: transformer
decoder_conf:
attention_heads: 4
linear_units: 2048
num_blocks: 6
dropout_rate: 0.1
positional_dropout_rate: 0.1
self_attention_dropout_rate: 0.
src_attention_dropout_rate: 0.
# 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 # label smoothing option
length_normalized_loss: false
# optimization related
accum_grad: 2
grad_clip: 5
max_epoch: 180
val_scheduler_criterion:
- valid
- acc
best_model_criterion:
- - valid
- acc
- max
keep_nbest_models: 10
optim: adam
optim_conf:
lr: 0.001
weight_decay: 0.000001
scheduler: warmuplr
scheduler_conf:
warmup_steps: 35000
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:
data_names: speech,text
data_types: sound,text
shuffle: True
shuffle_conf:
shuffle_size: 2048
sort_size: 500
batch_conf:
batch_type: token
batch_size: 16000
num_workers: 8
log_interval: 50
normalize: None

5
egs/aishell/branchformer/run.sh
View File

@ -46,10 +46,7 @@ train_set=train
valid_set=dev
test_sets="dev test"
#asr_config=conf/train_asr_branchformer.yaml
#asr_config=conf/train_asr_branchformer_bs16000.yaml
asr_config=conf/train_asr_branchformer_bs16000_gc2.yaml
#asr_config=conf/train_asr_branchformer_bs10000.yaml
asr_config=conf/train_asr_branchformer.yaml
model_dir="baseline_$(basename "${asr_config}" .yaml)_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer.yaml

101
egs/aishell/e_branchformer/conf/train_asr_e_branchformer_bs16000.yaml
View File

@ -1,101 +0,0 @@
# network architecture
# encoder related
encoder: e_branchformer
encoder_conf:
output_size: 256
attention_heads: 4
attention_layer_type: rel_selfattn
pos_enc_layer_type: rel_pos
rel_pos_type: latest
cgmlp_linear_units: 1024
cgmlp_conv_kernel: 31
use_linear_after_conv: false
gate_activation: identity
num_blocks: 12
dropout_rate: 0.1
positional_dropout_rate: 0.1
attention_dropout_rate: 0.1
input_layer: conv2d
layer_drop_rate: 0.0
linear_units: 1024
positionwise_layer_type: linear
use_ffn: true
macaron_ffn: true
merge_conv_kernel: 31
# decoder related
decoder: transformer
decoder_conf:
attention_heads: 4
linear_units: 2048
num_blocks: 6
dropout_rate: 0.1
positional_dropout_rate: 0.1
self_attention_dropout_rate: 0.
src_attention_dropout_rate: 0.
# 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 # label smoothing option
length_normalized_loss: false
# optimization related
accum_grad: 1
grad_clip: 5
max_epoch: 180
best_model_criterion:
- - valid
- acc
- max
keep_nbest_models: 10
optim: adam
optim_conf:
lr: 0.001
weight_decay: 0.000001
scheduler: warmuplr
scheduler_conf:
warmup_steps: 35000
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:
data_names: speech,text
data_types: sound,text
shuffle: True
shuffle_conf:
shuffle_size: 2048
sort_size: 500
batch_conf:
batch_type: token
batch_size: 16000
num_workers: 8
log_interval: 50
normalize: None

3
egs/aishell/e_branchformer/run.sh
View File

@ -46,8 +46,7 @@ train_set=train
valid_set=dev
test_sets="dev test"
#asr_config=conf/train_asr_e_branchformer.yaml
asr_config=conf/train_asr_e_branchformer_bs16000.yaml
asr_config=conf/train_asr_e_branchformer.yaml
model_dir="baseline_$(basename "${asr_config}" .yaml)_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer.yaml