This report describes our submission to the fifth CHiME Challenge. The main technical points of our system include the deep learning based speech enhancement and separation, training data augmentation via different versions of the official training data, SNR-based array selection, front-end model fusion, acoustic model fusion, and language model fusion. Tested on the development test set, our best system for single-array track using official LM has yielded a 37.7% WER relative reduction over the results given by official baseline system.