计算机应用 ›› 2013, Vol. 33 ›› Issue (08): 2383-2386.

• 典型应用 • 上一篇    下一篇

音乐粗情感域中的软切割及分类方法

林景栋,王唯,廖孝勇   

  1. 重庆大学 自动化学院,重庆 400044
  • 收稿日期:2013-02-26 修回日期:2013-04-12 出版日期:2013-08-01 发布日期:2013-09-11
  • 通讯作者: 王唯
  • 作者简介:林景栋(1966-),男,福建宁德人,副教授,博士,主要研究方向:音乐灯光表演控制系统、基于数据驱动的复杂工业流程状态识别和优化控制、智能家居控制系统检测设备;
    王唯(1989-),男,湖北远安人,硕士研究生,主要研究方向:音乐灯光表演控制系统;
    廖孝勇(1980-),男,重庆梁平人,讲师,博士,主要研究方向:音乐灯光表演控制系统、智能交通系统、企业信息化、先进制造系统。
  • 基金资助:
    重庆市自然科学基金资助项目

Method for music soft-cutting and classification in rough-emotion area

LINJingdong ,WANG Wei,LIAO Xiaoyong   

  1. School of Automation, Chongqing University, Chongqing 400044, China
  • Received:2013-02-26 Revised:2013-04-12 Online:2013-09-11 Published:2013-08-01
  • Contact: WANG Wei

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。

关键词: 音乐特征, 音乐情感, 情感识别, 小波分析, Mallat算法

Abstract: 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.

Key words: music feature, music emotion, emotion detection, wavelet analysis, Mallat algorithm

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