added RESULTS.md

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jinzr 2024-03-11 10:59:32 +08:00
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| `transducer_stateless_modified` | Conformer | Embedding + Conv1d | with modified transducer from `optimized_transducer` |
| `transducer_stateless_modified-2` | Conformer | Embedding + Conv1d | with modified transducer from `optimized_transducer` + extra data |
| `pruned_transducer_stateless3` | Conformer (reworked) | Embedding + Conv1d | pruned RNN-T + reworked model with random combiner + using aidatatang_20zh as extra data|
| `pruned_transducer_stateless7` | Zipformer | Embedding | pruned RNN-T + zipformer encoder + stateless decoder with context-size 1 |
| `pruned_transducer_stateless7` | Zipformer | Embedding | pruned RNN-T + zipformer encoder + stateless decoder with context-size set to 1 |
| `zipformer` | Upgraded Zipformer | Embedding + Conv1d | The latest recipe with context-size set to 1 |
The decoder in `transducer_stateless` is modified from the paper
[Rnn-Transducer with Stateless Prediction Network](https://ieeexplore.ieee.org/document/9054419/).

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politics, education, culture, lifestyle and family domains, covering a wide range of topics.
Manuscript can be found at: https://arxiv.org/abs/2201.02419
# Transducers
| | Encoder | Decoder | Comment |
|---------------------------------------|---------------------|--------------------|-----------------------------|
| `zipformer` | Upgraded Zipformer | Embedding + Conv1d | The latest recipe with context-size set to 1 |
The decoder is modified from the paper
[Rnn-Transducer with Stateless Prediction Network](https://ieeexplore.ieee.org/document/9054419/).
We place an additional Conv1d layer right after the input embedding layer.

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## Results
#### Zipformer
See <https://github.com/k2-fsa/icefall/pull/1537>
[./zipformer](./zipformer)
##### normal-scaled model, number of model parameters: 74470867, i.e., 74.47 M
| | test | valid | comment |
|------------------------|------|-------|-----------------------------------------|
| greedy search | 7.45 | 7.51 | --epoch 45 --avg 35 |
| modified beam search | 6.68 | 6.73 | --epoch 45 --avg 35 |
| fast beam search | 7.22 | 7.28 | --epoch 45 --avg 35 |
The training command:
```
export CUDA_VISIBLE_DEVICES="0,1,2,3"
./zipformer/train.py \
--world-size 4 \
--start-epoch 1 \
--num-epochs 50 \
--use-fp16 1 \
--exp-dir ./zipformer/exp \
--max-duration 1000
```
The decoding command:
```
./zipformer/decode.py \
--epoch 45 \
--avg 35 \
--exp-dir ./zipformer/exp \
--decoding-method greedy_search # modified_beam_search
```
The pretrained model is available at: https://huggingface.co/zrjin/icefall-asr-mdcc-zipformer-2024-03-11/