The project is associated with the recently-launched ICASSP 2022 Multi-channel Multi-party Meeting Transcription Challenge (M2MeT) to provide participants with baseline systems for speech recognition and speaker diarization in conference scenario.

Overview

M2MeT challenge baseline -- AliMeeting

This project provides the baseline system recipes for the ICASSP 2020 Multi-channel Multi-party Meeting Transcription Challenge (M2MeT). The challenge mainly consists of two tracks, named Automatic Speech Recognition (ASR) and Speaker Diarization. For each track, detailed descriptions can be found in its corresponding directory. The goal of this project is to simplify the training and evaluation procedures and make it flexible for participants to reproduce the baseline experiments and develop novelty methods.

Setup

git clone https://github.com/yufan-aslp/AliMeeting.git

Introduction

General steps

  1. Prepare the training data for speaker diarization and ASR model, respectively
  2. Follow the running steps of the speaker diarization experiment and obtain the rttm file. The rttm file includes the voice activity detection (VAD) and speaker diarization results, which will be used to compute the final Diarization Error Rate (DER) scores.
  3. For ASR track, we can train the single-speaker or multi-speaker ASR models. The evaluation metric of ASR systems is Character Error Rate (CER).

Citation

If you use the challenge dataset or our baseline systems, please consider citing the following:

@article{yu2021m2met,
title={M2MeT: The ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Challenge},
author={Yu, Fan and Zhang, Shiliang and Fu, Yihui and Xie, Lei and Zheng, Siqi and Du, Zhihao and Huang, Weilong and Guo, Pengcheng and Yan, Zhijie and Ma, Bin and others},
journal={arXiv preprint arXiv:2110.07393},
year={2021}
}

Our paper is available at https://arxiv.org/abs/2110.07393

The data download method will be sent to registered challenge participants via email.

Organizing Committee

Contributors

Code license

Apache 2.0

Owner
yufan
yufan
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