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3.4 KiB
3.4 KiB
Results (CER)
2022-12-09
Zipformer (pruned_transducer_stateless7)
Zipformer 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).
All the results below are using a single model that is trained by combining the following data: IHM, IHM+reverb, SDM, and GSS-enhanced MDM. Speed perturbation and MUSAN noise augmentation are applied on top of the pooled data.
WERs for IHM:
eval | test | comment | |
---|---|---|---|
greedy search | 10.13 | 12.21 | --epoch 15 --avg 8 --max-duration 500 |
modified beam search | 9.58 | 11.53 | --epoch 15 --avg 8 --max-duration 500 --beam-size 4 |
fast beam search | 9.92 | 12.07 | --epoch 15 --avg 8 --max-duration 500 --beam-size 4 --max-contexts 4 --max-states 8 |
WERs for SDM:
eval | test | comment | |
---|---|---|---|
greedy search | 23.70 | 26.41 | --epoch 15 --avg 8 --max-duration 500 |
modified beam search | 23.37 | 25.85 | --epoch 15 --avg 8 --max-duration 500 --beam-size 4 |
fast beam search | 23.60 | 26.38 | --epoch 15 --avg 8 --max-duration 500 --beam-size 4 --max-contexts 4 --max-states 8 |
WERs for GSS-enhanced MDM:
eval | test | comment | |
---|---|---|---|
greedy search | 12.24 | 14.99 | --epoch 15 --avg 8 --max-duration 500 |
modified beam search | 11.82 | 14.22 | --epoch 15 --avg 8 --max-duration 500 --beam-size 4 |
fast beam search | 12.30 | 14.98 | --epoch 15 --avg 8 --max-duration 500 --beam-size 4 --max-contexts 4 --max-states 8 |
The training command for reproducing is given below:
export CUDA_VISIBLE_DEVICES="0,1,2,3"
./pruned_transducer_stateless7/train.py \
--world-size 4 \
--num-epochs 15 \
--exp-dir pruned_transducer_stateless7/exp \
--max-duration 300 \
--max-cuts 100 \
--prune-range 5 \
--lr-factor 5 \
--lm-scale 0.25 \
--use-fp16 True
The decoding command is:
# greedy search
./pruned_transducer_stateless7/decode.py \
--epoch 15 \
--avg 8 \
--exp-dir ./pruned_transducer_stateless7/exp \
--max-duration 500 \
--decoding-method greedy_search
# modified beam search
./pruned_transducer_stateless7/decode.py \
--epoch 15 \
--avg 8 \
--exp-dir ./pruned_transducer_stateless7/exp \
--max-duration 500 \
--decoding-method modified_beam_search \
--beam-size 4
# fast beam search
./pruned_transducer_stateless7/decode.py \
--epoch 15 \
--avg 8 \
--exp-dir ./pruned_transducer_stateless5/exp \
--max-duration 500 \
--decoding-method fast_beam_search \
--beam 4 \
--max-contexts 4 \
--max-states 8
Pretrained model is available at https://huggingface.co/desh2608/icefall-asr-alimeeting-pruned-transducer-stateless7
The tensorboard training log can be found at https://tensorboard.dev/experiment/EzmVahMMTb2YfKWXwQ2dyQ/#scalars