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Recent development of speech processing, such as speech recognition, speakerdiarization, etc., has inspired numerous applications of speech technologies.The meeting scenario is one of the most valuable and, at the same time, mostchallenging scenarios for the deployment of speech technologies. Specifically,two typical tasks, speaker diarization and multi-speaker automatic speechrecognition have attracted much attention recently. However, the lack of largepublic meeting data has been a major obstacle for the advancement of the field.Therefore, we make available the AliMeeting corpus, which consists of 120 hoursof recorded Mandarin meeting data, including far-field data collected by8-channel microphone array as well as near-field data collected by headsetmicrophone. Each meeting session is composed of 2-4 speakers with differentspeaker overlap ratio, recorded in rooms with different size. Along with thedataset, we launch the ICASSP 2022 Multi-channel Multi-party MeetingTranscription Challenge (M2MeT) with two tracks, namely speaker diarization andmulti-speaker ASR, aiming to provide a common testbed for meeting richtranscription and promote reproducible research in this field. In this paper weprovide a detailed introduction of the AliMeeting dateset, challenge rules,evaluation methods and baseline systems.

M2MeT: The ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Challenge