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音乐表达偏差(失歌症)量化评价分析

Quantitative evaluation analysis of musical expression bias(amusia)
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摘要 发音频率(音高)是衡量一个人唱歌好坏的重要标准,人们常说的“跑调”,则是发音频率相比于曲谱频率偏高或者偏低的现象.本工作从频谱分析出发,量化确定频率相对偏差.而后以随机采集的清唱片段为研究对象,总结出频率相对偏差近似服从均值为0,标准差为0.03507的正态分布的规律.根据分布规律,人们可以针对某个人定义音乐表达偏差,量化其演唱准确程度,本项目提出的方法也为指标化失歌症提出了一个具有可行性的算法. The singing frequency(pitch)is an important criterion for measuring the singer's singing ability.The“tone deafness”is the phenomenon that a singer’s singing frequencies are higher or lower than the music frequencies.Based on the spectrum analysis the relative deviation of the frequency is quantitated determined.With the randomly collected cappella records as the research object,the relative deviation of the frequency approximately follow a normal distribution with mean 0 and standard deviation 0.03507.Thus,it is possible to define the“musical expression deviation”for each singer by providing scores of singing precision and to propose a feasible algorithm in evaluations of amusia.
作者 牛徐策 刘彦迪 李胡林 李永徽 NIU Xu-ce;LIU Yan-di;LI Hu-lin;LI Yong-hui(Department of Physics,School of Science,Tianjin University,Tianjin 300354,China;Grand Research Center of Social Science,Sanya,Hainan 572022,China)
出处 《大学物理》 2020年第7期66-70,共5页 College Physics
基金 国家自然科学基金(11804248) 天津市自然科学基金(18JCQNJC03200)资助。
关键词 频谱分析 跑调 失歌症 统计规律 机器学习 spectrum analysis tone deafness amusia statistical rule machine learning
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