To improve the performance of automatic labelling system, the context-dependent demiphone unit was proposed. A phone is divided into two parts: a left demiphone that accounts for the left side coarticulation and a right demiphone that copes with the right side context. Demiphone unit provides a better training of the transition between phones. In this paper, If the length of the phone is less than 120 msec, it is split into two demiphones. If the length of the phone is greater than 120 msec, it is divided into three parts. In order to evaluate the performance of the system, we use 452 phonetically balanced words(PBW) database for training and testing phoneme models. According to the experiment, the system using proposed demiphone unit compared with that using old demiphone unit gains 3.83% improved result(71.63%) within 10ms of the duo boundary, and 2.20% improved result(86.41%) within 20ms of the true boundary.