Traditionally, phone error detector uses a posterior probability as confidence measure, the correctness of a phone can be decided by comparing it to its corresponding threshold. In this thesis, two systems better than baseline are proposed, both are phone error detectors based on MLP network. The main concept of MLP-based system is the introduction of multiple-dimension a posterior probability. Besides, the difference between the two proposed MLP system is their training data. Hope that we could improve the performance of the MLP network by utilizing its learning property and taking useful data as training data. At last, we test the error detecting performance of these three phone error detectors by the Mandarin corpus of foreign speakers.