Multi-Label Classification of Music into Emotions
Multi-Label Classification of Music into Emotions
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发表时间：
2008
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通讯作者：
Konstantinos Trohidis;Grigorios Tsoumakas;George M. Kalliris;I. Vlahavas
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作者：
Konstantinos Trohidis;Grigorios Tsoumakas;George M. Kalliris;I. Vlahavas
在本文中，音乐中的情感的自动检测建模为多标签分类任务，其中一段音乐可能属于一个以上的类。在这个任务中，四个算法进行了评估和比较。此外，几个音频特征的预测能力进行评估，使用一种新的多标签特征选择方法。实验是在Telemon-Watson-Clark模型的基础上，对593首歌曲进行的。结果提供了有趣的见解讨论的算法和功能的质量。
In this paper, the automated detection of emotion in music is modeled as a multilabel classification task, where a piece of music may belong to more than one class. Four algorithms are evaluated and compared in this task. Furthermore, the predictive power of several audio features is evaluated using a new multilabel feature selection method. Experiments are conducted on a set of 593 songs with 6 clusters of music emotions based on the Tellegen-Watson-Clark model. Results provide interesting insights into the quality of the discussed algorithms and features.