音乐粗情感域中的软切割及分类方法

摘要

针对音乐灯光表演控制系统无法自动获取其控制所需的音乐特征信息,结合传统的Arousal-Valence模型提出了一种可用于音乐灯光表演的音乐粗情感模型.针对此模型,通过小波分析中的Mallat算法提取比较项并采用强度、节奏比值判断法,对音乐片段进行两次“软切割”,再根据相应的产生式专家系统规则便能够很好地对其进行粗情感域中的分类及特征量提取.仿真结果表明,该方法能够有效地按音乐情感将音乐片段分类,同时能够提取出满足音乐灯光表演控制系统时域上对音乐分段时间节点的高精度要求.%In response to the issue that music-light show control system cannot automatically obtain the required music characteristic information,a kind of rough-emotion model which can be used for music-light performance was presented combined with the traditional Arousal-Valence model.In this model,the Mallat algorithm of wavelet analysis was used to extract comparative items and the ratio of judgment method of strength and rhythm was used to take two "soft-cutting" actions on music.Then the classification of music in the rough-emotion model and the extraction of music characteristic parameters could be achieved by the corresponding production rules of expert system.The simulation results show that the method can effectively classify music clips according to music emotion and extract characteristic elements.Meanwhile,these characteristic elements can satisfy the precision requirement of the music-light show control system on the time domain.