Speech segmentation is an indispensable basic work in speech recognition and speech synthesis, and its quality has a great impact on the following system. Although manual segmentation and labeling is of high accuracy, it is quite time-consuming and laborious, and requires domain experts to deal with. As a result, automatic speech segmentation has become a research hotspot in speech processing. Firstly, aiming at current progress of automatic speech segmentation, several different classification methods of speech segmentation were explained. The alignment-based methods and boundary detection-based methods were introduced respectively, and the neural network speech segmentation methods, which can be applied in the above two frameworks, were expounded in detail. Then, some new speech segmentation technologies based on the methods such as bio-inspiration signal and game theory were introduced, and the performance evaluation metrics widely used in the speech segmentation field were given, and these evaluation metrics were compared and analyzed. Finally, the above contents were summarized and the future important research directions of speech segmentation were put forward.