siweilian
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FunASR


			
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    <title>ASRU 2023 MULTI-CHANNEL MULTI-PARTY MEETING TRANSCRIPTION CHALLENGE 2.0 (M2MeT2.0) &#8212; m2met2  documentation</title>
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  <section id="asru-2023-multi-channel-multi-party-meeting-transcription-challenge-2-0-m2met2-0">
<h1>ASRU 2023 MULTI-CHANNEL MULTI-PARTY MEETING TRANSCRIPTION CHALLENGE 2.0 (M2MeT2.0)<a class="headerlink" href="#asru-2023-multi-channel-multi-party-meeting-transcription-challenge-2-0-m2met2-0" title="Permalink to this heading">¶</a></h1>
<p>Building on the success of the M2MeT challenge, we are delighted to propose the M2MeT2.0 challenge as a special session at ASRU2023.
To advance the current state-of-the-art in multi-talker automatic speech recognition, the M2MeT2.0 challenge proposes a speaker-attributed ASR task, comprising two sub-tracks: fixed and open training conditions.
To facilitate reproducible research, we provide a comprehensive overview of the dataset, challenge rules, evaluation metrics, and baseline systems.</p>
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