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Selected methods of parametrization in problem of automatic classification classical music from the Renaissance era against the classical works from other eras

机译:文艺复兴时期古典音乐自动分类与其他时代古典作品相对应的参数化选择方法

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In this article we present the results of our work in the field of automatic classification of classical music pieces. The studied works were compositions of classical music composed in four eras: Renaissance, Baroque, Classicism and Romanticism. In the work we described selected methods of parameterization of music files, so that they emphasize the characteristic of Renaissance. The parameters we use are of a horizontal nature, i.e. they do not penetrate the vertical structure of the piece (e.g. chords progression). We used a base of 571 works of classical music, both secular and religious. The files were stored in MusicXML format and contained 187 Renaissance pieces, 146 Baroque, 119 classics and 119 stylistically belonging to the Romantic era, respectively. The results of the studies were presented using 4, 13 and 113 parameters. An artificial neural network and Support Vector Machine were used to classify the era to which the song belongs.
机译:在本文中,我们介绍了古典乐曲自动分类领域的工作结果。所研究的作品是在四个时代(文艺复兴时期,巴洛克时期,古典主义和浪漫主义)创作的古典音乐作品。在工作中,我们描述了音乐文件参数化的选定方法,以便它们强调文艺复兴时期的特征。我们使用的参数是水平的,即它们不会穿透乐曲的垂直结构(例如和弦进行)。我们使用了571部世俗和宗教古典音乐作品作为基础。这些文件以MusicXML格式存储,分别包含187个文艺复兴时期作品,146个巴洛克风格,119个经典作品和119个风格上属于浪漫主义时代的作品。使用4、13和113个参数显示了研究结果。人工神经网络和支持向量机用于对歌曲所属的时代进行分类。

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