In this study, we have presented a speech vs nonspeech segmentation of audio signals extracted from video. We have used 4330 seconds of audio signal extracted from "Lost" TV series for training. Our training set is automatically builded by using timestamp information exists in subtitles. After that, silence areas within those speech areas are discarded with a further study. Then, standard deviation of MFCC feature vectors of size 20 have been obtained Finally, Support Vector Machines (SVM) is used with one-vs-all method for the classification.