---
language: zh-CN
datasets:
- aishell1
metrics:
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Large 53 - Chinese (zh-CN), by Yue Qin
  results:
  - task: 
      name: Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: AISHELL-1 zh-CN
      type: aishell1
      args: zh-CN
    metrics:
       - name: Test CER
         type: cer
         value: 7.04
---

# Wav2Vec2-Large-XLSR-53-Chinese-zh-CN-aishell1

Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Chinese using the [AISHELL-1](https://github.com/kaldi-asr/kaldi/tree/master/egs/aishell).
When using this model, make sure that your speech input is sampled at 16kHz.


**Test Result**:

In the table below I report the Character Error Rate (CER) of the model. I ran the evaluation script described above. 

| Model | CER | CER-with-LM |
| ------------- | ------------- | ------------- |
| qinyue/wav2vec2-large-xlsr-53-chinese-zn-cn-aishell1 | **7.04%** | **3.96%** |