摘要
在数字音乐的研究应用中,大多数高层语义的音乐特征研究都以MIDI音乐文件库作为素材,其中主旋律音轨作为最重要的音乐信息,而从MIDI文件中获取主旋律信息具有很大的难度和误差.提出一种应用随机森林的方法自动抽取MIDI文件中主旋律所在的音轨.首先根据信息熵理论定义了音轨特征的熵值,并通过实验判断该特征的熵值对区分MIDI主旋律音轨与伴奏音轨是有效的.然后由MIDI文件的音轨信息熵和一些其他重要特征组成特征向量,构建随机森林分类器抽取MIDI文件主旋律所在的音轨.由实验可知,该模型有较高的准确率,对提取MIDI文件主旋律音轨有效.
In the digital musical research and applications, MIDI music files are used as materials for most of music high-level semantic features research. And the melody is the most important information. However,it is great difficulty to get melodic track information. This paper represented a method to extract melodic track from midiraeks files based on random forests classifier. First,the information entropy of midi-track was defined based on information entropy theory. By test experiment,it was proved its validity to dis- criminate melodic track from accompaniment track. Then, the information entropy combined with other important midi-track features were used to construct the feature vector. Random forest classifier was used in the paper to classify midi tracks. According to experiments,the accuracy of melodic track extraction is quite good. The method can extract melodic track from MIDI file effectively.
出处
《厦门大学学报(自然科学版)》
CAS
CSCD
北大核心
2010年第1期43-46,共4页
Journal of Xiamen University:Natural Science