This paper describes a discriminative-based training approach to continuous phone recognition. Recently minimum phone error (MPE) training is widely used to enhance the performance of large vocabulary continuous speech recognition, but few of them applied it to continuous phone recognition. In this paper, we explore a flexible combination of the sausage net with the MPE training. Furthermore, a more effective method of MPE weight update is introduced. The best experimental result in this study indicates that our approach achieves 7% error rate reduction when comparing to the baseline system. This demonstrates the advantages of the proposed approach for the MPE training. Keywords: minimum phone error, discriminative training, continuous phone recognition, sausage, speech recognition.