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基于内容的音乐信息提取的研究对象与思路

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摘要 基于内容的音乐信息提取(Content-Based Music Information Retrieval,CBMIR)是属于信息提取(Information Retrieval)的一个分支,CBMIR从媒体内容出发,利用音乐理论、声学心理学、信号处理技术和机器学习方法 ,试图解决数字音乐媒体急剧增长背景下的音乐特征分析和语义标定问题。文章通过对CBMIR的研究对象的分析,引出了CBMIR在特征维度、时间维度上的多层次的研究思路,并简要介绍了目前CBMIR的主流研究内容。
作者 黄镭 邓明
机构地区 广西广播电视大学教学资源中心
出处 《广西广播电视大学学报》 2015年第4期80-85,共6页 Journal of Guangxi Open University
关键词 内容 音乐信息 提取 机器学习
分类号 G434 [文化科学—教育技术学]
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参考文献14

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  • 3P. Hamel, S. Lemieux, Y. Bengio, and D. Eck, "Temporal Pooling and Multiscale Learning for Automatic Annotation and Ranking of Music Audio," in Proceedings of the 12th International Society for Mu- sic Information Retrieval Conference, ISMIR 2011, Mi- ami, Florida, USA, October 24-28, 2011,2011, pp. 729 - 734.
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广西广播电视大学学报
2015年 第4期

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