期刊文献+

层次分析法的电子音乐音质评估模型 被引量:2

Evaluation Model of Electronic Music Sound Quality Based on AHP
下载PDF
导出
摘要 为准确评估电子音乐音质,提出了基于层次分析法的电子音乐音质评估模型。首先将电子音乐音质评估作为目标层,将声源特性、信号特征、声场特性、听觉特性和立体感作为准则层,将十音质评估元素作为方案层,从而电子音乐音质评估指标体系结构,然后根据各层次间元素的从属关系或并列关系,构建电子音乐音质判断矩阵,通过判断矩阵的最大特征值归一化后特征向量分量,获取电子音乐音质评估指标体系各层元素的权重,最后采用电子音乐音质评估元素权重和专家评分,得到电子音乐音质评估结果。仿真测试结果表明,这种方法能获取各电子音乐音质评估元素对音质的影响权重,得到准确的电子音乐音质评估结果。 In order to evaluate the sound quality of electronic music accurately,an evaluation model based on AHP is proposed.Firstly,the electronic music quality evaluation is taken as the target layer,the sound source characteristics,signal characteristics,sound field characteristics,auditory characteristics and stereo sense as the criterion layer,and the ten sound quality evaluation elements are taken as the scheme layer.Thus,an electronic music quality evaluation index system structure is constructed.Then,according to the subordinate or parallel relationship between the elements of each level,the electronic music quality judgment matrix is constructed,through which the judgment can be made.After the maximum eigenvalue of the matrix is normalized,the eigenvector component is obtained to obtain the weight of the elements in each layer of the electronic music quality evaluation index system.Finally,the electronic music quality evaluation element weight and expert score are used to obtain the electronic music quality evaluation results.The simulation test results show that this method can obtain the weight of the influence of each evaluation element on the quality of electronic music,and get the accurate evaluation results of electronic music quality.
作者 梁惠恩 LIANG Hui’en(Department of Education and Education Technology, Jiangmen Vocational and Polytechnic College, Jiangmen 529000, China)
出处 《微型电脑应用》 2020年第3期157-160,共4页 Microcomputer Applications
基金 湖北教育厅项目(HBJY20187722)
关键词 层次分析法 电子音乐 音质评估 指标体系 判断矩阵 权重 Analytic hierarchy process Electronic music Acoustic quality evaluation Index system Judgment matrix Weights
  • 相关文献

参考文献10

二级参考文献48

  • 1jsoup, http://jsoup.org/, 2015.
  • 2ICTCLAS. http://www.ictclas.org/, 2015.
  • 3Lin P Y, Lin Z J, Kuang B Q, et a/. A short chinese text incremental clustering algorithm based on weighted semantics and naive Bayes. Journal of Computational Information Systems, 2012, 8(10): 4257-4268.
  • 4Hagan M T, Demuth H B, Beale M. Neural Network Design. PWS Pub Co, 2002.
  • 5Mitchell T. Machine Learning. Boston: MIP Press, 2002.
  • 6熊伟. 运筹学[M].3版. 北京:机械工业出版社, 2014.
  • 7ZHU J J. Research on several problems of analytic hierarchy process and its applications[ D ]. Shenyang: Northeastern Uni- versity, 2005 : 16-25 ( in Chinese ).
  • 8SAATY T L. Decision making for leaders : The analytical hierar- chy process for decisions in a complex world [ M ]. Belmont: Wadsworth, 1982:28-42.
  • 9GUO J Y,ZHANG Z B,SUN Q Y. Research and application on analytic hierarchy process [ J ]. China Safety Science Journal, 2008,18 ( 5 ) : 148-153 ( in Chinese).
  • 10WU D T,LI D F. The shortage and improvement approach for the analytic hierarchy process [ J ]. Journal of Beijing Normal University( Nature Science ), 2004,40 ( 2 ) : 264-268 ( in Chi- nese).

共引文献103

同被引文献17

引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部