mirror of
https://github.com/k2-fsa/icefall.git
synced 2025-08-10 02:22:17 +00:00
5aafbb970e
* initial commit for SPGISpeech recipe * add decoding * add spgispeech transducer * remove conformer ctc; minor fixes in RNN-T * add results * add tensorboard * add pretrained model to HF * remove unused scripts and soft link common scripts * remove duplicate files * pre commit hooks * remove change in librispeech * pre commit hook * add CER numbers
74 lines
2.4 KiB
Markdown
74 lines
2.4 KiB
Markdown
## Results
|
|
|
|
### SPGISpeech BPE training results (Pruned Transducer)
|
|
|
|
#### 2022-05-11
|
|
|
|
#### Conformer encoder + embedding decoder
|
|
|
|
Conformer encoder + non-current decoder. The decoder
|
|
contains only an embedding layer, a Conv1d (with kernel size 2) and a linear
|
|
layer (to transform tensor dim).
|
|
|
|
The WERs are
|
|
|
|
| | dev | val | comment |
|
|
|---------------------------|------------|------------|------------------------------------------|
|
|
| greedy search | 2.46 | 2.40 | --avg-last-n 10 --max-duration 500 |
|
|
| modified beam search | 2.28 | 2.24 | --avg-last-n 10 --max-duration 500 --beam-size 4 |
|
|
| fast beam search | 2.38 | 2.35 | --avg-last-n 10 --max-duration 500 --beam-size 4 --max-contexts 4 --max-states 8 |
|
|
|
|
**NOTE:** SPGISpeech transcripts can be prepared in `ortho` or `norm` ways, which refer to whether the
|
|
transcripts are orthographic or normalized. These WERs correspond to the normalized transcription
|
|
scenario.
|
|
|
|
The training command for reproducing is given below:
|
|
|
|
```
|
|
export CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7"
|
|
|
|
./pruned_transducer_stateless2/train.py \
|
|
--world-size 8 \
|
|
--num-epochs 20 \
|
|
--start-epoch 0 \
|
|
--exp-dir pruned_transducer_stateless2/exp \
|
|
--max-duration 200 \
|
|
--prune-range 5 \
|
|
--lr-factor 5 \
|
|
--lm-scale 0.25 \
|
|
--use-fp16 True
|
|
```
|
|
|
|
The decoding command is:
|
|
```
|
|
# greedy search
|
|
./pruned_transducer_stateless2/decode.py \
|
|
--iter 696000 --avg 10 \
|
|
--exp-dir ./pruned_transducer_stateless2/exp \
|
|
--max-duration 100 \
|
|
--decoding-method greedy_search
|
|
|
|
# modified beam search
|
|
./pruned_transducer_stateless2/decode.py \
|
|
--iter 696000 --avg 10 \
|
|
--exp-dir ./pruned_transducer_stateless2/exp \
|
|
--max-duration 100 \
|
|
--decoding-method modified_beam_search \
|
|
--beam-size 4
|
|
|
|
# fast beam search
|
|
./pruned_transducer_stateless2/decode.py \
|
|
--iter 696000 --avg 10 \
|
|
--exp-dir ./pruned_transducer_stateless2/exp \
|
|
--max-duration 1500 \
|
|
--decoding-method fast_beam_search \
|
|
--beam 4 \
|
|
--max-contexts 4 \
|
|
--max-states 8
|
|
```
|
|
|
|
Pretrained model is available at <https://huggingface.co/desh2608/icefall-asr-spgispeech-pruned-transducer-stateless2>
|
|
|
|
The tensorboard training log can be found at
|
|
<https://tensorboard.dev/experiment/ExSoBmrPRx6liMTGLu0Tgw/#scalars>
|