Lin, Jingru
The NUS-HLT System for ICASSP2024 ICMC-ASR Grand Challenge
Ge, Meng, Peng, Yizhou, Jiang, Yidi, Lin, Jingru, Ao, Junyi, Yildirim, Mehmet Sinan, Wang, Shuai, Li, Haizhou, Feng, Mengling
This paper summarizes our team's efforts in both tracks of the ICMC-ASR Challenge for in-car multi-channel automatic speech recognition. Our submitted systems for ICMC-ASR Challenge include the multi-channel front-end enhancement and diarization, training data augmentation, speech recognition modeling with multi-channel branches. Tested on the offical Eval1 and Eval2 set, our best system achieves a relative 34.3% improvement in CER and 56.5% improvement in cpCER, compared to the offical baseline system.