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FunASR


			
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    <title>Baseline &#8212; MULTI-PARTY MEETING TRANSCRIPTION CHALLENGE 2.0</title>
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<li class="toctree-l1"><a class="reference internal" href="Introduction.html">Introduction</a><ul>
<li class="toctree-l2"><a class="reference internal" href="Introduction.html#call-for-participation">Call for participation</a></li>
<li class="toctree-l2"><a class="reference internal" href="Introduction.html#timeline-aoe-time">Timeline(AOE Time)</a></li>
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<li class="toctree-l1"><a class="reference internal" href="Dataset.html">Datasets</a><ul>
<li class="toctree-l2"><a class="reference internal" href="Dataset.html#overview-of-training-data">Overview of training data</a></li>
<li class="toctree-l2"><a class="reference internal" href="Dataset.html#detail-of-alimeeting-corpus">Detail of AliMeeting corpus</a></li>
<li class="toctree-l2"><a class="reference internal" href="Dataset.html#get-the-data">Get the data</a></li>
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<li class="toctree-l1"><a class="reference internal" href="Track_setting_and_evaluation.html">Track &amp; Evaluation</a><ul>
<li class="toctree-l2"><a class="reference internal" href="Track_setting_and_evaluation.html#speaker-attributed-asr">Speaker-Attributed ASR</a></li>
<li class="toctree-l2"><a class="reference internal" href="Track_setting_and_evaluation.html#evaluation-metric">Evaluation metric</a></li>
<li class="toctree-l2"><a class="reference internal" href="Track_setting_and_evaluation.html#sub-track-arrangement">Sub-track arrangement</a></li>
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<li class="toctree-l1 current"><a class="current reference internal" href="#">Baseline</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#overview">Overview</a></li>
<li class="toctree-l2"><a class="reference internal" href="#quick-start">Quick start</a></li>
<li class="toctree-l2"><a class="reference internal" href="#baseline-results">Baseline results</a></li>
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  <section id="baseline">
<h1>Baseline<a class="headerlink" href="#baseline" title="Permalink to this heading">¶</a></h1>
<section id="overview">
<h2>Overview<a class="headerlink" href="#overview" title="Permalink to this heading">¶</a></h2>
<p>We will release an E2E SA-ASR baseline conducted on <a class="reference external" href="https://github.com/alibaba-damo-academy/FunASR">FunASR</a> at the time according to the timeline. The model architecture is shown in Figure 3. The SpeakerEncoder is initialized with a pre-trained speaker verification model from ModelScope. This speaker verification model is also be used to extract the speaker embedding in the speaker profile.</p>
<p><img alt="model archietecture" src="_images/sa_asr_arch.png" /></p>
</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 />
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
<span class="p">|</span>——<span class="w"> </span>Eval_Ali_far
<span class="p">|</span>——<span class="w"> </span>Eval_Ali_near
<span class="p">|</span>——<span class="w"> </span>Test_Ali_far
<span class="p">|</span>——<span class="w"> </span>Test_Ali_near
<span class="p">|</span>——<span class="w"> </span>Train_Ali_far
<span class="p">|</span>——<span class="w"> </span>Train_Ali_near
Before<span class="w"> </span>running<span class="w"> </span><span class="sb">`</span>run_m2met_2023_infer.sh<span class="sb">`</span>,<span class="w"> </span>you<span class="w"> </span>need<span class="w"> </span>to<span class="w"> </span>place<span class="w"> </span>the<span class="w"> </span>new<span class="w"> </span><span class="nb">test</span><span class="w"> </span><span class="nb">set</span><span class="w"> </span><span class="sb">`</span>Test_2023_Ali_far<span class="sb">`</span><span class="w"> </span><span class="o">(</span>to<span class="w"> </span>be<span class="w"> </span>released<span class="w"> </span>after<span class="w"> </span>the<span class="w"> </span>challenge<span class="w"> </span>starts<span class="o">)</span><span class="w"> </span><span class="k">in</span><span class="w"> </span>the<span class="w"> </span><span class="sb">`</span>./dataset<span class="sb">`</span><span class="w"> </span>directory,<span class="w"> </span>which<span class="w"> </span>contains<span class="w"> </span>only<span class="w"> </span>raw<span class="w"> </span>audios.<span class="w"> </span>Then<span class="w"> </span>put<span class="w"> </span>the<span class="w"> </span>given<span class="w"> </span><span class="sb">`</span>wav.scp<span class="sb">`</span>,<span class="w"> </span><span class="sb">`</span>wav_raw.scp<span class="sb">`</span>,<span class="w"> </span><span class="sb">`</span>segments<span class="sb">`</span>,<span class="w"> </span><span class="sb">`</span>utt2spk<span class="sb">`</span><span class="w"> </span>and<span class="w"> </span><span class="sb">`</span>spk2utt<span class="sb">`</span><span class="w"> </span><span class="k">in</span><span class="w"> </span>the<span class="w"> </span><span class="sb">`</span>./data/Test_2023_Ali_far<span class="sb">`</span><span class="w"> </span>directory.<span class="w">  </span>
<span class="sb">```</span>shell
data/Test_2023_Ali_far
<span class="p">|</span>——<span class="w"> </span>wav.scp
<span class="p">|</span>——<span class="w"> </span>wav_raw.scp
<span class="p">|</span>——<span class="w"> </span>segments
<span class="p">|</span>——<span class="w"> </span>utt2spk
<span class="p">|</span>——<span class="w"> </span>spk2utt
</pre></div>
</div>
<p>For more details you can see <a class="reference external" href="https://github.com/alibaba-damo-academy/FunASR/blob/main/egs/alimeeting/sa-asr/README.md">here</a></p>
</section>
<section id="baseline-results">
<h2>Baseline results<a class="headerlink" href="#baseline-results" title="Permalink to this heading">¶</a></h2>
<p>The results of the baseline system are shown in Table 3. The speaker profile adopts the oracle speaker embedding during training. However, due to the lack of oracle speaker label during evaluation, the speaker profile provided by an additional spectral clustering is used. Meanwhile, the results of using the oracle speaker profile on Eval and Test Set are also provided to show the impact of speaker profile accuracy.</p>
<p><img alt="baseline result" src="_images/baseline_result.png" /></p>
</section>
</section>


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