关键词: 流行音乐结构分析, 人声发现, 支持向量机

Abstract: Facing the problem of vocal discrimination in pop music，the authors propose applying MFCC parameters as features，and Support Vector Machine（SVM） as classifier.Due to the continuity of audio signal features，the authors consider low-pass filtering to the classification results as post-processing.Experiment results show that at frame level，a quite promising classification accuracy of 85.76% can be obtained.It is also revealed that singers with different languages have large vocal differences in pronunciation， especially in MFCC feature statistics.The classification results may be used as a similarity measure for music structure analysis in the future work.

Key words: pop music structure analysis, Vocal/Non-vocal discrimination, Support Vector Machine（SVM）