Summary On The ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Grand Challenge

TL;DR

The paper summarizes the ICASSP 2022 M2MeT challenge, which focuses on multi-channel multi-party meeting transcription, providing datasets, challenge setups, baseline results, and key techniques used in submissions.

Contribution

It introduces a new Mandarin multi-party meeting dataset and details the challenge tracks, setups, and baseline results, advancing research in multi-party speech transcription.

Findings

Released 120 hours of Mandarin meeting data with annotations

Summarized challenge results and techniques used in submissions

Provided baselines for speaker diarization and ASR tasks

Abstract

The ICASSP 2022 Multi-channel Multi-party Meeting Transcription Grand Challenge (M2MeT) focuses on one of the most valuable and the most challenging scenarios of speech technologies. The M2MeT challenge has particularly set up two tracks, speaker diarization (track 1) and multi-speaker automatic speech recognition (ASR) (track 2). Along with the challenge, we released 120 hours of real-recorded Mandarin meeting speech data with manual annotation, including far-field data collected by 8-channel microphone array as well as near-field data collected by each participants' headset microphone. We briefly describe the released dataset, track setups, baselines and summarize the challenge results and major techniques used in the submissions.