Music Genre Classification by Ensembles of Audio and Lyrics Features
Music Genre Classification by Ensembles of Audio and Lyrics Features
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按音频和歌词特征的组合进行音乐流派分类
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
A. Rauber
中科院分区：
文献类型：
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作者：
Rudolf Mayer;A. Rauber
算法可以理解和解释音乐的特征，并将它们组织起来并推荐给用户，这对于处理私人和商业收藏的日益增长的规模都有很大的帮助。音乐本质上是一种多模态的数据类型，与音乐相关的歌词与音频一样，对歌曲的接收和信息至关重要。在本文中，我们提出了如何将音乐的歌词领域与声学领域相结合的先进方法。我们通过音乐信息检索中的一个常见任务——音乐类型分类来评估我们的方法。在之前的工作中，简单的特征融合显示了改进，我们应用了更复杂的结果（或后期）融合方法。我们获得的结果优于单个特征集上单个算法的最佳选择。
Algorithms that can understand and interpret characteristics of music, and organise them for and recommend them to their users can be of great assistance in handling the ever growing size of both private and commercial collections. Music is an inherently multi-modal type of data, and the lyrics associated with the music are as essential to the reception and the message of a song as is the audio. In this paper, we present advanced methods on how the lyrics domain of music can be combined with the acoustic domain. We evaluate our approach by means of a common task in music information retrieval, musical genre classification. Advancing over previous work that showed improvements with simple feature fusion, we apply the more sophisticated approach of result (or late) fusion. We achieve results superior to the best choice of a single algorithm on a single feature set.