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

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