Several features for discrimination between vocal sounds and other environmental sounds

Several features are found to discriminate between the vocals sounds and other environmental sounds. The vocal sounds include speaking, laughter, etc., 23 kinds of nonverbal and verbal sounds; and the environmental sounds are recorded in domestic environments. The discriminative features are selected from 22 kinds of features. They are the speech recognition features of LPCC and MFCC, time-spectral features from FFT, statistics of pitch values and contour, ratio of voiced and unvoiced segments, and spectrum of pitch contour. The 9 features calculated from pitch contours perform much better than the features calculated from spectrums, which show no discriminability. The classification is performed simply by a neural network to evaluate the performance of the 9 features. They are tested on a 21 CDs environmental sound database. And the hit rate of 9 8.7 3% with the false alarm rate of 11 % are obtained. The classification result confirms the effectiveness and efficiency of the features.