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</section>
<section id="quick-start">
<h2>Quick start<a class="headerlink" href="#quick-start" title="Permalink to this heading"></a></h2>
<p>To run the baseline, first you need to install FunASR and ModelScope. (<a class="reference external" href="https://alibaba-damo-academy.github.io/FunASR/en/installation.html">installation</a>)<br />
<p>To run the baseline, first you need to install FunASR and ModelScope. (<a class="reference external" href="https://github.com/alibaba-damo-academy/FunASR#installation">installation</a>)<br />
There are two startup scripts, <code class="docutils literal notranslate"><span class="pre">run.sh</span></code> for training and evaluating on the old eval and test sets, and <code class="docutils literal notranslate"><span class="pre">run_m2met_2023_infer.sh</span></code> for inference on the new test set of the Multi-Channel Multi-Party Meeting Transcription 2.0 (<a class="reference external" href="https://alibaba-damo-academy.github.io/FunASR/m2met2/index.html">M2MeT2.0</a>) Challenge.<br />
Before running <code class="docutils literal notranslate"><span class="pre">run.sh</span></code>, you must manually download and unpack the <a class="reference external" href="http://www.openslr.org/119/">AliMeeting</a> corpus and place it in the <code class="docutils literal notranslate"><span class="pre">./dataset</span></code> directory:</p>
<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>dataset

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![model archietecture](images/sa_asr_arch.png)
## Quick start
To run the baseline, first you need to install FunASR and ModelScope. ([installation](https://alibaba-damo-academy.github.io/FunASR/en/installation.html))
To run the baseline, first you need to install FunASR and ModelScope. ([installation](https://github.com/alibaba-damo-academy/FunASR#installation))
There are two startup scripts, `run.sh` for training and evaluating on the old eval and test sets, and `run_m2met_2023_infer.sh` for inference on the new test set of the Multi-Channel Multi-Party Meeting Transcription 2.0 ([M2MeT2.0](https://alibaba-damo-academy.github.io/FunASR/m2met2/index.html)) Challenge.
Before running `run.sh`, you must manually download and unpack the [AliMeeting](http://www.openslr.org/119/) corpus and place it in the `./dataset` directory:
```shell

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![model archietecture](images/sa_asr_arch.png)
## 快速开始
首先需要安装FunASR和ModelScope. ([installation](https://alibaba-damo-academy.github.io/FunASR/en/installation.html))
首先需要安装FunASR和ModelScope. ([installation](https://github.com/alibaba-damo-academy/FunASR#installation))
基线系统有训练和测试两个脚本,`run.sh`是用于训练基线系统并在M2MeT的验证与测试集上评估的，而`run_m2met_2023_infer.sh`用于此次竞赛预备开放的全新测试集上测试同时生成符合竞赛最终提交格式的文件。
在运行 `run.sh`前，需要自行下载并解压[AliMeeting](http://www.openslr.org/119/)数据集并放置于`./dataset`目录下：
```shell

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</section>
<section id="id3">
<h2>快速开始<a class="headerlink" href="#id3" title="此标题的永久链接"></a></h2>
<p>首先需要安装FunASR和ModelScope. (<a class="reference external" href="https://alibaba-damo-academy.github.io/FunASR/en/installation.html">installation</a>)<br />
<p>首先需要安装FunASR和ModelScope. (<a class="reference external" href="https://github.com/alibaba-damo-academy/FunASR#installation">installation</a>)<br />
基线系统有训练和测试两个脚本,<code class="docutils literal notranslate"><span class="pre">run.sh</span></code>是用于训练基线系统并在M2MeT的验证与测试集上评估的，而<code class="docutils literal notranslate"><span class="pre">run_m2met_2023_infer.sh</span></code>用于此次竞赛预备开放的全新测试集上测试同时生成符合竞赛最终提交格式的文件。
在运行 <code class="docutils literal notranslate"><span class="pre">run.sh</span></code>前，需要自行下载并解压<a class="reference external" href="http://www.openslr.org/119/">AliMeeting</a>数据集并放置于<code class="docutils literal notranslate"><span class="pre">./dataset</span></code>目录下：</p>
<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>dataset