Model |
Params |
GPUS |
Averaged Model |
Config |
Augmentation |
Loss |
transformer |
32.52M |
8 Tesla V100-SXM2-32GB |
10-best val_loss |
conf/transformer.yaml |
spec_aug |
6.3197922706604 |
Test Set |
Decode Method |
#Snt |
#Wrd |
Corr |
Sub |
Del |
Ins |
Err |
S.Err |
test-clean |
attention |
2620 |
52576 |
96.4 |
2.5 |
1.1 |
0.4 |
4.0 |
34.7 |
test-clean |
ctc_greedy_search |
2620 |
52576 |
95.9 |
3.7 |
0.4 |
0.5 |
4.6 |
48.0 |
test-clean |
ctc_prefix_beamsearch |
2620 |
52576 |
95.9 |
3.7 |
0.4 |
0.5 |
4.6 |
47.6 |
test-clean |
attention_rescore |
2620 |
52576 |
96.8 |
2.9 |
0.3 |
0.4 |
3.7 |
38.0 |
Test Set |
Decode Method |
#Snt |
#Wrd |
Corr |
Sub |
Del |
Ins |
Err |
S.Err |
test-clean |
join_ctc_only_att |
2620 |
52576 |
96.1 |
2.5 |
1.4 |
0.4 |
4.4 |
34.7 |
test-clean |
join_ctc_w/o_lm |
2620 |
52576 |
97.2 |
2.6 |
0.3 |
0.4 |
3.2 |
34.9 |
test-clean |
join_ctc_w_lm |
2620 |
52576 |
97.9 |
1.8 |
0.2 |
0.3 |
2.4 |
27.8 |
Compare with ESPNET
we using 8gpu, but model size (aheads4-adim256) small than it.