The USTC-NERCSLIP Systems for the CHiME-7 DASR Challenge

Ruoyu Wang; Maokui He; Jun Du; Hengshun Zhou; Shutong Niu; Hang Chen; Yanyan Yue; Gaobin Yang; Shilong Wu; Lei Sun; Yanhui Tu; Haitao Tang; Shuangqing Qian; Tian Gao; Mengzhi Wang; Genshun Wan; Jia Pan; Jianqing Gao; Chin-Hui Lee

arXiv · 2308.14638

The USTC-NERCSLIP Systems for the CHiME-7 DASR Challenge

Ruoyu Wang·Maokui He·Jun Du·Hengshun Zhou·Shutong Niu·Hang Chen·Yanyan Yue·Gaobin Yang·Shilong Wu·Lei Sun·Yanhui Tu·Haitao Tang·Shuangqing Qian·Tian Gao·Mengzhi Wang·Genshun Wan·Jia Pan·Jianqing Gao·Chin-Hui Lee

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Abstract

This technical report details our submission system to the CHiME-7 DASR Challenge, which focuses on speaker diarization and speech recognition under complex multi-speaker scenarios. Additionally, it also evaluates the efficiency of systems in handling diverse array devices. To address these issues, we implemented an end-to-end speaker diarization system and introduced a rectification strategy based on multi-channel spatial information. This approach significantly diminished the word error rates (WER). In terms of recognition, we utilized publicly available pre-trained models as the foundational models to train our end-to-end speech recognition models. Our system attained a Macro-averaged diarization-attributed WER (DA-WER) of 21.01% on the CHiME-7 evaluation set, which signifies a relative improvement of 62.04% over the official baseline system.

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Ruoyu Wang, Maokui He, Jun Du, Hengshun Zhou, Shutong Niu, Hang Chen, Yanyan Yue, Gaobin Yang, Shilong Wu, Lei Sun, Yanhui Tu, Haitao Tang, Shuangqing Qian, Tian Gao, Mengzhi Wang, Genshun Wan, Jia Pan, Jianqing Gao, Chin-Hui Lee. 2023-08-28. The USTC-NERCSLIP Systems for the CHiME-7 DASR Challenge. https://arxiv.org/abs/2308.14638

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