The CHiME-7 DASR Challenge: Distant Meeting Transcription with Multiple Devices in Diverse Scenarios

Samuele Cornell; Matthew Wiesner; Shinji Watanabe; Desh Raj; Xuankai Chang; Paola Garcia; Matthew Maciejewski; Yoshiki Masuyama; Zhong-Qiu Wang; Stefano Squartini; Sanjeev Khudanpur

arXiv · 2306.13734

The CHiME-7 DASR Challenge: Distant Meeting Transcription with Multiple Devices in Diverse Scenarios

Samuele Cornell·Matthew Wiesner·Shinji Watanabe·Desh Raj·Xuankai Chang·Paola Garcia·Matthew Maciejewski·Yoshiki Masuyama·Zhong-Qiu Wang·Stefano Squartini·Sanjeev Khudanpur

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Abstract

The CHiME challenges have played a significant role in the development and evaluation of robust automatic speech recognition (ASR) systems. We introduce the CHiME-7 distant ASR (DASR) task, within the 7th CHiME challenge. This task comprises joint ASR and diarization in far-field settings with multiple, and possibly heterogeneous, recording devices. Different from previous challenges, we evaluate systems on 3 diverse scenarios: CHiME-6, DiPCo, and Mixer 6. The goal is for participants to devise a single system that can generalize across different array geometries and use cases with no a-priori information. Another departure from earlier CHiME iterations is that participants are allowed to use open-source pre-trained models and datasets. In this paper, we describe the challenge design, motivation, and fundamental research questions in detail. We also present the baseline system, which is fully array-topology agnostic and features multi-channel diarization, channel selection, guided source separation and a robust ASR model that leverages self-supervised speech representations (SSLR).

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Samuele Cornell, Matthew Wiesner, Shinji Watanabe, Desh Raj, Xuankai Chang, Paola Garcia, Matthew Maciejewski, Yoshiki Masuyama, Zhong-Qiu Wang, Stefano Squartini, Sanjeev Khudanpur. 2023-06-23. The CHiME-7 DASR Challenge: Distant Meeting Transcription with Multiple Devices in Diverse Scenarios. https://arxiv.org/abs/2306.13734

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