This paper establishs CTC-based systems on Chinese Mandarin ASR task, three different level output units are explored: characters, context independent phonemes and context dependent phoneme. To make training stable we propose Newbob-Trn strategy, furthermore, blank label prior cost is proposed to improve the performance. Further, we establish the CTC-trained UniLSTM-RC model, which ensures the real-time requirement of an online system, meanwhile, brings performance gain on Chinese Mandarin ASR task.