基于改进蚁群—模糊聚类算法的电影背景音乐情感分类

Emotion Classification of Movie Background Music Based on Improved Ant Colony and Fuzzy Clustering Algorithm

为提高电影情感内容分析的准确率,需要对电影的背景音乐进行情感的自动分类,为此提出改进蚁群-模糊聚类算法的音乐情感分类方法,分析改进蚁群-模糊聚类算法的基本原理及实现步骤,并以500首电影音乐数据为例,对该数据进行挖掘分析,使用改进蚁群-聚类算法对平均音高、平均音强、旋律的方向、音高的稳定值、节奏的强弱规律和节拍6个情感特征向量进行聚类。试验效果表明取得很好的聚类效果。

In order to improve the accuracy of film affective content analysis,movie background music emotion automatic classification needs to be done. This paper puts forward the improved ant colony fuzzy clustering algorithm of music emotion classification method. Firstly,the paper analyzes the basic principle of the improved ant colony fuzzy clustering algorithm and the implementation steps,and then taking 500 pieces of film music data as an example for the data analysis and data mining,clusters the data using improved ant colony clustering algorithm on the pitch＇s average value,average intensity,stability of melody,pitch,rhythm changes in the strength of the beat and six emotional feature vector. The results of the test show that the proposed method is in good agreement with the actual results;and has achieved a higher clustering forecast performance.