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Results
Zh-En datasets bpe-based training results (Non-streaming) on Zipformer model
This is the pull request #1238 in icefall.
Non-streaming (Byte-Level BPE vocab_size=2000)
Best results (num of params : ~69M):
The training command:
./zipformer/train.py \
--world-size 4 \
--num-epochs 35 \
--use-fp16 1 \
--max-duration 1000 \
--num-workers 8
The decoding command:
for method in greedy_search modified_beam_search fast_beam_search; do
./zipformer/decode.py \
--epoch 34 \
--avg 19 \
--decoding_method $method
done
Word Error Rates (WERs) listed below are produced by the checkpoint of the 20th epoch using greedy search and BPE model (# tokens is 2000).
Datasets | TAL-CSASR | TAL-CSASR |
---|---|---|
Zipformer WER (%) | dev | test |
greedy_search | 6.65 | 6.69 |
modified_beam_search | 6.46 | 6.51 |
fast_beam_search | 6.57 | 6.68 |
Pre-trained model can be found here : https://huggingface.co/zrjin/icefall-asr-zipformer-multi-zh-en-2023-11-22, which is trained on LibriSpeech 960-hour training set (with speed perturbation), TAL-CSASR training set (with speed perturbation) and AiShell-2 (w/o speed perturbation).