---
tasks:
- language-score-prediction
domain:
- audio
model-type:
- autoregressive
frameworks:
- pytorch
backbone:
- transformer
metrics:
- PPL
license: Apache License 2.0
language:
- cn
tags:
- FunASR
- Ngram
- Alibaba
datasets:
  train:
  - 1G OpenSource text
  test:
  - SpeechIO TIOBE
indexing:
   results:
   - task:
       name: Automatic Speech Recognition
widgets:
  - task: language-score-prediction
    inputs:
      - type: text
        name: input
        title: 文本
    examples:
      - name: 1
        title: 示例1
        inputs:
          - name: input
            data: 'hello 大 家 好 呀'
    inferencespec:
      cpu: 1 #CPU数量
      memory: 4096
---

# 模型介绍

## Highlights
模型为使用开源数据aishell、wenetspeech文本训练的Ngram模型编译得到的FST模型，可以直接用来做生产部署，一键部署教程（[点击此处](https://github.com/alibaba-damo-academy/FunASR/blob/main/funasr/runtime/readme_cn.md)）


## <strong>[ModelScope-FunASR](https://github.com/alibaba-damo-academy/FunASR)</strong>
<strong>[FunASR](https://github.com/alibaba-damo-academy/FunASR)</strong>提供可便捷本地或者云端服务器部署的离线文件转写服务，内核为FunASR已开源runtime-SDK。 集成了达摩院语音实验室在Modelscope社区开源的语音端点检测(VAD)、Paraformer-large语音识别(ASR)、标点恢复(PUNC) 等相关能力，拥有完整的语音识别链路，可以将几十个小时的音频或视频识别成带标点的文字，而且支持上百路请求同时进行转写。

[**最新动态**](https://github.com/alibaba-damo-academy/FunASR#whats-new) 
| [**环境安装**](https://github.com/alibaba-damo-academy/FunASR#installation)
| [**介绍文档**](https://alibaba-damo-academy.github.io/FunASR/en/index.html)
| [**服务部署**](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime)
| [**模型库**](https://github.com/alibaba-damo-academy/FunASR/blob/main/docs/model_zoo/modelscope_models.md)
| [**联系我们**](https://github.com/alibaba-damo-academy/FunASR#contact)




## 快速上手

### 服务端启动

下载部署工具`funasr-runtime-deploy-offline-cpu-zh.sh`

```shell
curl -O https://raw.githubusercontent.com/alibaba-damo-academy/FunASR/main/funasr/runtime/deploy_tools/funasr-runtime-deploy-offline-cpu-zh.sh;
# 如遇到网络问题，中国大陆用户，可以用个下面的命令：
# curl -O https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/shell/funasr-runtime-deploy-offline-cpu-zh.sh;
```

执行部署工具，在提示处输入回车键即可完成服务端安装与部署。目前便捷部署工具暂时仅支持Linux环境，其他环境部署参考开发指南（[点击此处](https://alibaba-damo-academy.github.io/FunASR/en/funasr/runtime/docs/SDK_tutorial_zh.html)）
```shell
sudo bash funasr-runtime-deploy-offline-cpu-zh.sh install --workspace ./funasr-runtime-resources
```

### 客户端测试与使用

运行上面安装指令后，会在./funasr-runtime-resources（默认安装目录）中下载客户端测试工具目录samples（[下载点击此处](https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/sample/funasr_samples.tar.gz)），
我们以Python语言客户端为例，进行说明，支持多种音频格式输入（.wav, .pcm, .mp3等），也支持视频输入(.mp4等)，以及多文件列表wav.scp输入，其他版本客户端请参考文档（[点击此处](https://alibaba-damo-academy.github.io/FunASR/en/funasr/runtime/docs/SDK_tutorial_zh.html#id5)）

```shell
python3 wss_client_asr.py --host "127.0.0.1" --port 10095 --mode offline --audio_in "../audio/asr_example.wav"
```

更详细用法介绍（[点击此处](https://github.com/alibaba-damo-academy/FunASR/blob/main/funasr/runtime/docs/SDK_tutorial_zh.md)）

## 相关论文以及引用信息

```BibTeX
@inproceedings{chen2020controllable,
  title={Controllable Time-Delay Transformer for Real-Time Punctuation Prediction and Disfluency Detection},
  author={Chen, Qian and Chen, Mengzhe and Li, Bo and Wang, Wen},
  booktitle={ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={8069--8073},
  year={2020},
  organization={IEEE}
}
```