Abstract: A novel mapping of embedding music to Rn space and a new kernel-based classification method are presented.First，analyzing melody contours from a huge music dataset，it translats music datasets to strings with an alphabet including only eight letters.Second，three string kernels are obtained by mapping music strings to high dimension Rn space using contiguous substrings embedding method.Finally，performances of three string kernels on five music datasets are evaluated by SVM algorithm and ROC graph.

摘要： 给出了一种新的映射音乐到Rn空间的方法和基于串核的音乐风格分类法。首先利用统计方法分析大量音乐的旋律轮廓线得到合适的编码模式，用它把旋律轮廓线编码为有限字母表（8个字母）的字符串。利用连续子串嵌入法把音乐串显式映射到高维Rn空间，并用核表示这一映射。通过用基于核的SVM分类算法和ROC评价方法，比较了3个不同串核在5组音乐数据集上的分类性能。