icefall/egs/multi_zh_en/ASR/RESULTS.md

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	AiShell-2	AiShell-2	LibriSpeech	LibriSpeech
Zipformer WER (%)	dev	test	dev	test	test-clean	test-other
greedy_search	6.65	6.69	6.57	7.03	2.43	5.70
modified_beam_search	6.46	6.51	6.18	6.60	2.41	5.57
fast_beam_search	6.57	6.68	6.40	6.74	2.40	5.56

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).