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# Paraformer-Large
- Model link:
- Model size: 45M
# Environments
- date: `Tue Feb 13 20:13:22 CST 2023`
- python version: `3.7.12`
- FunASR version: `0.1.0`
- pytorch version: `pytorch 1.7.0`
- Git hash: ``
- Commit date: ``
# Beachmark Results
## result (paper)
beam=20，CER tool：https://github.com/yufan-aslp/AliMeeting
| model | Para (M) | Data (hrs) | Eval (CER%) | Test (CER%) |
|:-------------------:|:---------:|:---------:|:---------:| :---------:|
| MFCCA | 45 | 917 | 16.1 | 17.5 |
## result（modelscope）
beam=10
with separating character (src)
| model | Para (M) | Data (hrs) | Eval_sp (CER%) | Test_sp (CER%) |
|:-------------------:|:---------:|:---------:|:---------:| :---------:|
| MFCCA | 45 | 917 | 17.1 | 18.6 |
without separating character (src)
| model | Para (M) | Data (hrs) | Eval_nosp (CER%) | Test_nosp (CER%) |
|:-------------------:|:---------:|:---------:|:---------:| :---------:|
| MFCCA | 45 | 917 | 16.4 | 18.0 |
## 偏差
Considering the differences of the CER calculation tool and decoding beam size, the results of CER are biased (<0.5%).
