Triplecq 3b40d9bbb1
Zipformer recipe for ReazonSpeech (#1611)
* Add first cut at ReazonSpeech recipe

This recipe is mostly based on egs/csj, but tweaked to the point that
can be run with ReazonSpeech corpus.

Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>

---------

Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>
Co-authored-by: Fujimoto Seiji <fujimoto@ceptord.net>
Co-authored-by: Chen <qc@KDM00.cm.cluster>
Co-authored-by: root <root@KDA01.cm.cluster>
2024-06-13 14:19:03 +08:00

1.3 KiB

Results

Zipformer

Non-streaming

large-scaled model, number of model parameters: 159337842, i.e., 159.34 M
decoding method In-Distribution CER JSUT CommonVoice TEDx comment
greedy search 4.2 6.7 7.84 17.9 --epoch 39 --avg 7
modified beam search 4.13 6.77 7.69 17.82 --epoch 39 --avg 7

The training command is:

./zipformer/train.py \
  --world-size 8 \
  --num-epochs 40 \
  --start-epoch 1 \
  --use-fp16 1 \
  --exp-dir zipformer/exp-large \
  --causal 0 \
  --num-encoder-layers 2,2,4,5,4,2 \
  --feedforward-dim 512,768,1536,2048,1536,768 \
  --encoder-dim 192,256,512,768,512,256 \
  --encoder-unmasked-dim 192,192,256,320,256,192 \
  --lang data/lang_char \
  --max-duration 1600 

The decoding command is:

./zipformer/decode.py \
    --epoch 40 \
    --avg 16 \
    --exp-dir zipformer/exp-large \
    --max-duration 600 \
    --causal 0 \
    --decoding-method greedy_search \
    --num-encoder-layers 2,2,4,5,4,2 \
    --feedforward-dim 512,768,1536,2048,1536,768 \
    --encoder-dim 192,256,512,768,512,256 \
    --encoder-unmasked-dim 192,192,256,320,256,192 \
    --lang data/lang_char \
    --blank-penalty 0