The CHiME-7 DASR Challenge: Distant Meeting Transcription with Multiple Devices in Diverse Scenarios
Cornell, Samuele, Wiesner, Matthew, Watanabe, Shinji, Raj, Desh, Chang, Xuankai, Garcia, Paola, Maciejewski, Matthew, Masuyama, Yoshiki, Wang, Zhong-Qiu, Squartini, Stefano, Khudanpur, Sanjeev
–arXiv.org Artificial Intelligence
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).
arXiv.org Artificial Intelligence
Jul-14-2023
- Country:
- Asia > Japan (0.14)
- Europe > Italy (0.14)
- North America > United States (0.14)
- Genre:
- Research Report (0.90)
- Technology:
- Information Technology > Artificial Intelligence
- Machine Learning (1.00)
- Natural Language (0.93)
- Speech > Speech Recognition (1.00)
- Information Technology > Artificial Intelligence