docs

游雁

2024-05-30 6d3a3da8a8c7d1be9740a9b2d6fac767f8dfff17

 README.md

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([简体中文](./README_zh.md)|English)

# FunASR: A Fundamental End-to-End Speech Recognition Toolkit
[//]: # (# FunASR: A Fundamental End-to-End Speech Recognition Toolkit)

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[![PyPI](https://img.shields.io/pypi/v/funasr)](https://pypi.org/project/funasr/)

@@ -59,18 +60,26 @@
<a name="Installation"></a>
## Installation

- Requirements
```text
python>=3.8
torch>=1.13
torchaudio
```

- Install for pypi
```shell
pip3 install -U funasr
```
Or install from source code
- Or install from source code
``` sh
git clone https://github.com/alibaba/FunASR.git && cd FunASR
pip3 install -e ./
```
Install modelscope for the pretrained models (Optional)
- Install modelscope or huggingface_hub for the pretrained models (Optional)

```shell
pip3 install -U modelscope
pip3 install -U modelscope huggingface_hub
```

## Model Zoo
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```
Note: `chunk_size` is the configuration for streaming latency.` [0,10,5]` indicates that the real-time display granularity is `10*60=600ms`, and the lookahead information is `5*60=300ms`. Each inference input is `600ms` (sample points are `16000*0.6=960`), and the output is the corresponding text. For the last speech segment input, `is_final=True` needs to be set to force the output of the last word.

<details><summary>More Examples</summary>

### Voice Activity Detection (Non-Streaming)
```python
from funasr import AutoModel
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res = model.generate(input=(wav_file, text_file), data_type=("sound", "text"))
print(res)
```


### Speech Emotion Recognition
```python
from funasr import AutoModel

model = AutoModel(model="emotion2vec_plus_large")

wav_file = f"{model.model_path}/example/test.wav"

res = model.generate(wav_file, output_dir="./outputs", granularity="utterance", extract_embedding=False)
print(res)
```

More usages ref to [docs](docs/tutorial/README_zh.md), 
more examples ref to [demo](https://github.com/alibaba-damo-academy/FunASR/tree/main/examples/industrial_data_pretraining)

</details>

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