The CHiME-7 DASR Challenge: Distant Meeting Transcription with Multiple Devices in Diverse Scenarios
Samuele Cornell, Matthew S. Wiesner, Shinji Watanabe, Desh Raj, Xuankai Chang, Leibny Paola Garcia, Yoshiki Masuyam, Zhong-Qiu Wang, Stefano Squartini, Sanjeev Khudanpur
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).