speech_recognition/FunASR
1
0
Fork 0
mirror of https://github.com/modelscope/FunASR synced 2025-09-15 14:48:36 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity

Usage

Browse Source
This commit is contained in:
游雁 2023-06-26 14:52:08 +08:00
parent 1bc89cab1b
commit aa031509a7
1 changed files with 51 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

56
README.md
View File

@ -12,7 +12,7 @@
[**News**](https://github.com/alibaba-damo-academy/FunASR#whats-new)
| [**Highlights**](#highlights)
| [**Installation**](#installation)
| [**Docs**](https://alibaba-damo-academy.github.io/FunASR/en/index.html)
| [**Usage**](#usage)
| [**Papers**](https://github.com/alibaba-damo-academy/FunASR#citations)
| [**Runtime**](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime)
| [**Model Zoo**](https://github.com/alibaba-damo-academy/FunASR/blob/main/docs/model_zoo/modelscope_models.md)
@ -44,22 +44,68 @@ Or install from source code
``` sh
git clone https://github.com/alibaba/FunASR.git && cd FunASR
pip install -e ./
pip3 install -e ./
# For the users in China, you could install with the command:
# pip install -e ./ -i https://mirror.sjtu.edu.cn/pypi/web/simple
# pip3 install -e ./ -i https://mirror.sjtu.edu.cn/pypi/web/simple
```
If you want to use the pretrained models in ModelScope, you should install the modelscope:
```shell
pip install -U modelscope
pip3 install -U modelscope
# For the users in China, you could install with the command:
# pip install -U modelscope -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html -i https://mirror.sjtu.edu.cn/pypi/web/simple
# pip3 install -U modelscope -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html -i https://mirror.sjtu.edu.cn/pypi/web/simple
```
For more details, please ref to [installation](https://alibaba-damo-academy.github.io/FunASR/en/installation/installation.html)
## Usage
You could use FunASR by:
- egs
- egs_modelscope
- runtime
### egs
If you want to train the model from scratch, you could use funasr directly by recipe, as the following:
```shell
cd egs/aishell/paraformer
. ./run.sh --CUDA_VISIBLE_DEVICES="0,1" --gpu_num=2
```
More examples could be found in [docs](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_pipeline/quick_start.html)
### egs_modelscope
If you want to infer or finetune pretraining models from modelscope, you could use funasr by modelscope pipeline, as the following:
```python
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
inference_pipeline = pipeline(
task=Tasks.auto_speech_recognition,
model='damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch',
)
rec_result = inference_pipeline(audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav')
print(rec_result)
# {'text': '欢迎大家来体验达摩院推出的语音识别模型'}
```
More examples could be found in [docs](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_pipeline/quick_start.html)
### runtime
An example with websocket:
For the server:
```shell
python wss_srv_asr.py --port 10095
```
For the client:
```shell
python wss_client_asr.py --host "0.0.0.0" --port 10095 --mode 2pass --chunk_size "5,10,5"
#python wss_client_asr.py --host "0.0.0.0" --port 10095 --mode 2pass --chunk_size "8,8,4" --audio_in "./data/wav.scp" --output_dir "./results"
```
More examples could be found in [docs](https://alibaba-damo-academy.github.io/FunASR/en/runtime/websocket_python.html#id2)
## Contact
If you have any questions about FunASR, please contact us by