update funasr-runtime-sdk-gpu-0.1.1

雾聪

2024-07-01 31bf3a88a09f6e7c895224f4dc75e8f2c138d5c8

 README_zh.md

@@ -2,7 +2,11 @@

(简体中文|[English](./README.md))

# FunASR: A Fundamental End-to-End Speech Recognition Toolkit


[![SVG Banners](https://svg-banners.vercel.app/api?type=origin&text1=FunASR🤠&text2=💖%20A%20Fundamental%20End-to-End%20Speech%20Recognition%20Toolkit&width=800&height=210)](https://github.com/Akshay090/svg-banners)

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

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

@@ -29,10 +33,17 @@

<a name="最新动态"></a>
## 最新动态
- 2024/07/01：中文离线文件转写服务GPU版本 1.1发布，优化bladedisc模型兼容性问题；详细信息参阅([部署文档](runtime/readme_cn.md))
- 2024/06/27：中文离线文件转写服务GPU版本 1.0发布，支持动态batch，支持多路并发，在长音频测试集上单线RTF为0.0076，多线加速比为1200+（CPU为330+）；详细信息参阅([部署文档](runtime/readme_cn.md))
- 2024/05/15：新增加情感识别模型，[emotion2vec+large](https://modelscope.cn/models/iic/emotion2vec_plus_large/summary)，[emotion2vec+base](https://modelscope.cn/models/iic/emotion2vec_plus_base/summary)，[emotion2vec+seed](https://modelscope.cn/models/iic/emotion2vec_plus_seed/summary)，输出情感类别为：生气/angry，开心/happy，中立/neutral，难过/sad。
- 2024/05/15: 中文离线文件转写服务 4.5、英文离线文件转写服务 1.6、中文实时语音听写服务 1.10 发布，适配FunASR 1.0模型结构；详细信息参阅([部署文档](runtime/readme_cn.md))
- 2024/03/05：新增加Qwen-Audio与Qwen-Audio-Chat音频文本模态大模型，在多个音频领域测试榜单刷榜，中支持语音对话，详细用法见 [示例](examples/industrial_data_pretraining/qwen_audio)。
- 2024/03/05：新增加Whisper-large-v3模型支持，多语言语音识别/翻译/语种识别，支持从 [modelscope](examples/industrial_data_pretraining/whisper/demo.py)仓库下载，也支持从 [openai](examples/industrial_data_pretraining/whisper/demo_from_openai.py)仓库下载模型。
- 2024/03/05: 中文离线文件转写服务 4.4、英文离线文件转写服务 1.5、中文实时语音听写服务 1.9 发布，docker镜像支持arm64平台，升级modelscope版本；详细信息参阅([部署文档](runtime/readme_cn.md))
- 2024/01/30：funasr-1.0发布，更新说明[文档](https://github.com/alibaba-damo-academy/FunASR/discussions/1319)

<details><summary>展开日志</summary>

- 2024/01/30：新增加情感识别 [模型链接](https://www.modelscope.cn/models/iic/emotion2vec_base_finetuned/summary)，原始模型 [repo](https://github.com/ddlBoJack/emotion2vec).
- 2024/01/25: 中文离线文件转写服务 4.2、英文离线文件转写服务 1.3，优化vad数据处理方式，大幅降低峰值内存占用，内存泄漏优化；中文实时语音听写服务 1.7 发布，客户端优化；详细信息参阅([部署文档](runtime/readme_cn.md))
- 2024/01/09: funasr社区软件包windows 2.0版本发布，支持软件包中文离线文件转写4.1、英文离线文件转写1.2、中文实时听写服务1.6的最新功能，详细信息参阅([FunASR社区软件包windows版本](https://www.modelscope.cn/models/damo/funasr-runtime-win-cpu-x64/summary))
@@ -50,21 +61,33 @@
- 2023.07.17: BAT一种低延迟低内存消耗的RNN-T模型发布，详细信息参阅（[BAT](egs/aishell/bat)）
- 2023.06.26: ASRU2023 多通道多方会议转录挑战赛2.0完成竞赛结果公布，详细信息参阅（[M2MeT2.0](https://alibaba-damo-academy.github.io/FunASR/m2met2_cn/index.html)）

</details>

<a name="安装教程"></a>
## 安装教程

- 安装funasr之前，确保已经安装了下面依赖环境:
```text
python>=3.8
torch>=1.13
torchaudio
```

- pip安装
```shell
pip3 install -U funasr
```
或者从源代码安装

- 或者从源代码安装
``` sh
git clone https://github.com/alibaba/FunASR.git && cd FunASR
pip3 install -e ./
```
如果需要使用工业预训练模型，安装modelscope（可选）

如果需要使用工业预训练模型，安装modelscope与huggingface_hub（可选）

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

## 模型仓库
@@ -74,19 +97,20 @@
（注：⭐ 表示ModelScope模型仓库，🤗 表示Huggingface模型仓库，🍀表示OpenAI模型仓库）


|                                                                                                     模型名字                                                                                                      |        任务详情        |     训练数据     | 参数量  | 
|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------:|:------------:|:----:|
|    paraformer-zh <br> ([⭐](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary)  [🤗](https://huggingface.co/funasr/paraformer-tp) )    |  语音识别，带时间戳输出，非实时   |  60000小时，中文  | 220M |
| paraformer-zh-streaming <br> ( [⭐](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/summary) [🤗](https://huggingface.co/funasr/paraformer-zh-streaming) ) |      语音识别，实时       |  60000小时，中文  | 220M |
|         paraformer-en <br> ( [⭐](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/summary) [🤗](https://huggingface.co/funasr/paraformer-en) )         |      语音识别，非实时      |  50000小时，英文  | 220M |
|                      conformer-en <br> ( [⭐](https://modelscope.cn/models/damo/speech_conformer_asr-en-16k-vocab4199-pytorch/summary) [🤗](https://huggingface.co/funasr/conformer-en) )                      |      语音识别，非实时      |  50000小时，英文  | 220M |
|                        ct-punc <br> ( [⭐](https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary) [🤗](https://huggingface.co/funasr/ct-punc) )                         |        标点恢复        |  100M，中文与英文  | 1.1G | 
|                            fsmn-vad <br> ( [⭐](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) [🤗](https://huggingface.co/funasr/fsmn-vad) )                             |     语音端点检测，实时      | 5000小时，中文与英文 | 0.4M | 
|                              fa-zh <br> ( [⭐](https://modelscope.cn/models/damo/speech_timestamp_prediction-v1-16k-offline/summary) [🤗](https://huggingface.co/funasr/fa-zh) )                               |      字级别时间戳预测      |  50000小时，中文  | 38M  |
|                                 cam++ <br> ( [⭐](https://modelscope.cn/models/iic/speech_campplus_sv_zh-cn_16k-common/summary) [🤗](https://huggingface.co/funasr/campplus) )                                 |      说话人确认/分割      |    5000小时    | 7.2M | 
|                                     Whisper-large-v3 <br> ([⭐](https://www.modelscope.cn/models/iic/Whisper-large-v3/summary)  [🍀](https://github.com/openai/whisper) )                                      |  语音识别，带时间戳输出，非实时   |     多语言      |  1G  |
|                                         Qwen-Audio <br> ([⭐](examples/industrial_data_pretraining/qwen_audio/demo.py)  [🤗](https://huggingface.co/Qwen/Qwen-Audio) )                                         |  音频文本多模态大模型（预训练）   |     多语言      |  8B  |
|                   Qwen-Audio-Chat <br> ([⭐](examples/industrial_data_pretraining/qwen_audio/demo_chat.py)  [🤗](https://huggingface.co/Qwen/Qwen-Audio-Chat) )                                                | 音频文本多模态大模型（chat版本） |     多语言      |  8B  |
|                                                                                                     模型名字                                                                                                      |        任务详情        |      训练数据      |  参数量   | 
|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------:|:--------------:|:------:|
|    paraformer-zh <br> ([⭐](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary)  [🤗](https://huggingface.co/funasr/paraformer-zh) )    |  语音识别，带时间戳输出，非实时   |   60000小时，中文   |  220M  |
| paraformer-zh-streaming <br> ( [⭐](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/summary) [🤗](https://huggingface.co/funasr/paraformer-zh-streaming) ) |      语音识别，实时       |   60000小时，中文   |  220M  |
|         paraformer-en <br> ( [⭐](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/summary) [🤗](https://huggingface.co/funasr/paraformer-en) )         |      语音识别，非实时      |   50000小时，英文   |  220M  |
|                      conformer-en <br> ( [⭐](https://modelscope.cn/models/damo/speech_conformer_asr-en-16k-vocab4199-pytorch/summary) [🤗](https://huggingface.co/funasr/conformer-en) )                      |      语音识别，非实时      |   50000小时，英文   |  220M  |
|                        ct-punc <br> ( [⭐](https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary) [🤗](https://huggingface.co/funasr/ct-punc) )                         |        标点恢复        |   100M，中文与英文   |  290M  | 
|                            fsmn-vad <br> ( [⭐](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) [🤗](https://huggingface.co/funasr/fsmn-vad) )                             |     语音端点检测，实时      |  5000小时，中文与英文  |  0.4M  | 
|                              fa-zh <br> ( [⭐](https://modelscope.cn/models/damo/speech_timestamp_prediction-v1-16k-offline/summary) [🤗](https://huggingface.co/funasr/fa-zh) )                               |      字级别时间戳预测      |   50000小时，中文   |  38M   |
|                                 cam++ <br> ( [⭐](https://modelscope.cn/models/iic/speech_campplus_sv_zh-cn_16k-common/summary) [🤗](https://huggingface.co/funasr/campplus) )                                 |      说话人确认/分割      |     5000小时     |  7.2M  | 
|                                     Whisper-large-v3 <br> ([⭐](https://www.modelscope.cn/models/iic/Whisper-large-v3/summary)  [🍀](https://github.com/openai/whisper) )                                      |  语音识别，带时间戳输出，非实时   |      多语言       | 1550 M |
|                                         Qwen-Audio <br> ([⭐](examples/industrial_data_pretraining/qwen_audio/demo.py)  [🤗](https://huggingface.co/Qwen/Qwen-Audio) )                                         |  音频文本多模态大模型（预训练）   |      多语言       |   8B   |
|                                 Qwen-Audio-Chat <br> ([⭐](examples/industrial_data_pretraining/qwen_audio/demo_chat.py)  [🤗](https://huggingface.co/Qwen/Qwen-Audio-Chat) )                                  | 音频文本多模态大模型（chat版本） |      多语言       |   8B   |
|                        emotion2vec+large <br> ([⭐](https://modelscope.cn/models/iic/emotion2vec_plus_large/summary)  [🤗](https://huggingface.co/emotion2vec/emotion2vec_plus_large) )                        |    情感识别模型          | 40000小时，4种情感类别 |  300M  |

<a name="快速开始"></a>
## 快速开始
@@ -144,6 +168,8 @@
```

注：`chunk_size`为流式延时配置，`[0,10,5]`表示上屏实时出字粒度为`10*60=600ms`，未来信息为`5*60=300ms`。每次推理输入为`600ms`（采样点数为`16000*0.6=960`），输出为对应文字，最后一个语音片段输入需要设置`is_final=True`来强制输出最后一个字。

<details><summary>更多例子</summary>

### 语音端点检测（非实时）
```python
@@ -208,9 +234,24 @@
res = model.generate(input=(wav_file, text_file), data_type=("sound", "text"))
print(res)
```

### 情感识别
```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)
```

更详细（[教程文档](docs/tutorial/README_zh.md)），
更多（[模型示例](https://github.com/alibaba-damo-academy/FunASR/tree/main/examples/industrial_data_pretraining)）

</details>

## 导出ONNX
### 从命令行导出
```shell