A Robust Speech/Music Discrimination Approach
Xiaoping Feng · Audio Engineering · 2009
A new system for classifying audio segments as speech or music is presented.The system selects the features with the highest classification accuracy and corresponding SNR value.The value of this features extracted from each window-level segment are compared to certain thresholds, which are also adapted to the SNR.Multiexpert method of combining the features is employed to improve the classification accuracy.A new feature, the variance of low-band energy ratio, is also introduced, which produces large improvements in classification accuracy at low SNR.Performance of the proposed system is evaluated for different SNR.The experiment results show that the classification accuracy is excellent.