Music Mood Visualization Using Self-Organizing Maps

被引：13
|
作者：
Plewa, Magdalena [1 ]
Kostek, Bozena [1 ]
机构：
[1] Gdansk Univ Technol, Fac Elect Telecommun & Informat, Audio Acoust Lab, PL-81233 Gdansk, Poland
来源：
ARCHIVES OF ACOUSTICS | 2015年 / 40卷 / 04期
关键词：
music mood; music parameterization; MER (Music Emotion Recognition); MIR (Music Information Retrieval); Multidimensional Scaling (MDS); Principal Component Analysis (PCA); Self-Organizing Maps (SOM); ANN (Artificial Neural Networks); CLASSIFICATION; RECOGNITION; SIMILARITY; GENRE; SOUND;
D O I：
10.1515/aoa-2015-0051
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
Due to an increasing amount of music being made available in digital form in the Internet, an automatic organization of music is sought. The paper presents an approach to graphical representation of mood of songs based on Self-Organizing Maps. Parameters describing mood of music are proposed and calculated and then analyzed employing correlation with mood dimensions based on the Multidimensional Scaling. A map is created in which music excerpts with similar mood are organized next to each other on the two-dimensional display.
引用
收藏
页码：513 / 525
页数：13
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