Automatic Music Labeling Algorithm based on Tag Depth Analysis

Xiaochen Guo, Shihui Du
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Abstract

With the rapid development of music social media, online music resources are rapidly increasing and music types are increasingly diversified. As an effective means to organize massive music data, rich music annotation information has become an important part of online music services. Automatic music tagging algorithm based on tag depth analysis is an automatic music tagging method that uses the concept of tag depth to classify songs. The algorithm starts with a set of songs, where each song is assigned one or more tags. The lengths of these markers are then compared and assigned to different categories. For example, if a song has three tags, it will be classified as pop / rock, dance and country music. If the song uses two tags, it will be classified as rock / pop and pop / rock, respectively. This process will continue until all songs have been classified by their tag depth and classified accordingly.
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基于标签深度分析的音乐自动标注算法
随着音乐社交媒体的快速发展,网络音乐资源迅速增加,音乐类型日益多样化。丰富的音乐标注信息作为组织海量音乐数据的有效手段,已成为在线音乐服务的重要组成部分。基于标签深度分析的自动音乐标注算法是一种利用标签深度的概念对歌曲进行分类的自动音乐标注方法。该算法从一组歌曲开始,每首歌曲被分配一个或多个标签。然后比较这些标记的长度并将其分配到不同的类别。例如,如果一首歌有三个标签,它将被分类为流行/摇滚、舞蹈和乡村音乐。如果歌曲使用两个标签,它将分别被分类为摇滚/流行和流行/摇滚。这个过程将继续进行,直到所有歌曲都按照标签深度进行分类。
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