Merge pull request #867 from LittleChenCc/develop

update the results of TIMIT and Ted-ST
pull/870/head
Hui Zhang 3 years ago committed by GitHub
commit 84f77ecdf5
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@ -113,7 +113,8 @@ class U2STBaseModel(nn.Layer):
asr_weight: float=0.0,
ignore_id: int=IGNORE_ID,
lsm_weight: float=0.0,
length_normalized_loss: bool=False):
length_normalized_loss: bool=False,
**kwargs):
assert 0.0 <= ctc_weight <= 1.0, ctc_weight
super().__init__()
@ -650,7 +651,7 @@ class U2STModel(U2STBaseModel):
odim=vocab_size,
enc_n_units=encoder.output_size(),
blank_id=0,
dropout_rate=model_conf['ctc_dropout_rate'],
dropout_rate=model_conf['ctc_dropoutrate'],
reduction=True, # sum
batch_average=True, # sum / batch_size
grad_norm_type=model_conf['ctc_grad_norm_type'])

@ -8,3 +8,8 @@
| data/manifest.train | 0.942 ~ 60 |
| data/manifest.dev | 1.151 ~ 39 |
| data/manifest.test | 1.1 ~ 42.746 |
## Transformer
| Model | Params | Config | Char-BLEU |
| --- | --- | --- | --- |
| Transformer+ASR MTL | 50.26M | conf/transformer_joint_noam.yaml | 17.38 |

@ -1,3 +1,11 @@
# TIMIT
Results will be organized and updated soon.
### Transformer
| Model | Params | Config | Decode method | PER |
| --- | --- | --- | --- | --- |
| transformer | 5.17M | conf/transformer.yaml | attention | 0.5531 |
| transformer | 5.17M | conf/transformer.yaml | ctc_greedy_search | 0.3922 |
| transformer | 5.17M | conf/transformer.yaml | ctc_prefix_beam_search | 0.3768 |

@ -3,12 +3,12 @@ data:
train_manifest: data/manifest.train
dev_manifest: data/manifest.dev
test_manifest: data/manifest.test
min_input_len: 0.5 # second
max_input_len: 30.0 # second
min_input_len: 0.0 # second
max_input_len: 10.0 # second
min_output_len: 0.0 # tokens
max_output_len: 400.0 # tokens
min_output_input_ratio: 0.05
max_output_input_ratio: 100.0
max_output_len: 150.0 # tokens
min_output_input_ratio: 0.005
max_output_input_ratio: 1000.0
collator:
vocab_filepath: data/vocab.txt
@ -42,10 +42,10 @@ model:
# encoder related
encoder: transformer
encoder_conf:
output_size: 256 # dimension of attention
output_size: 128 # dimension of attention
attention_heads: 4
linear_units: 2048 # the number of units of position-wise feed forward
num_blocks: 12 # the number of encoder blocks
linear_units: 1024 # the number of units of position-wise feed forward
num_blocks: 6 # the number of encoder blocks
dropout_rate: 0.1
positional_dropout_rate: 0.1
attention_dropout_rate: 0.0
@ -56,7 +56,7 @@ model:
decoder: transformer
decoder_conf:
attention_heads: 4
linear_units: 2048
linear_units: 1024
num_blocks: 6
dropout_rate: 0.1
positional_dropout_rate: 0.1
@ -65,26 +65,26 @@ model:
# hybrid CTC/attention
model_conf:
ctc_weight: 0.3
ctc_weight: 0.5
ctc_dropoutrate: 0.0
ctc_grad_norm_type: instance
ctc_grad_norm_type: batch
lsm_weight: 0.1 # label smoothing option
length_normalized_loss: false
training:
n_epoch: 120
n_epoch: 200
accum_grad: 2
global_grad_clip: 5.0
optim: adam
optim_conf:
lr: 0.002
lr: 0.004
weight_decay: 1e-06
scheduler: warmuplr # pytorch v1.1.0+ required
scheduler_conf:
warmup_steps: 400
warmup_steps: 2000
lr_decay: 1.0
log_interval: 100
log_interval: 10
checkpoint:
kbest_n: 50
latest_n: 5

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