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.
@article{arxiv.2312.16002,
title = {The NUS-HLT System for ICASSP2024 ICMC-ASR Grand Challenge},
author = {Meng Ge and Yizhou Peng and Yidi Jiang and Jingru Lin and Junyi Ao and Mehmet Sinan Yildirim and Shuai Wang and Haizhou Li and Mengling Feng},
journal= {arXiv preprint arXiv:2312.16002},
year = {2023}
}
Comments
Technical Report. 2 pages. For ICMC-ASR-2023 Challenge