In this paper, we propose a new speech detection method to English-Mandarin code-switching speech. Unlike previous methods, in this method we first train a support vector machine (SVM) model based on feature parameters and Gaussian Mixture Model (GMM) , then integrate the language identification (LID) information based on SVM model and acoustic information into the decoding process. Lastly, we develop a prototype system to present the method. Experiments proved that our method we can improve the accurancy of code-switching speech recognition at a certain degree compared with previous methods.