Machine sound classification has been one of the fundamental tasks of music technology. A major branch of sound classification is the classification of music genres. However, though covering most genres of music, existing music genre datasets often do not contain fine-grained labels that indicate the detailed sub-genres of music. In consideration of the consistency of genres of songs in a mixtape or in a DJ (live) set, we have collected and annotated a dataset of house music that provide 4 sub-genre labels, namely future house, bass house, progressive house and melodic house. Experiments show that our annotations well exhibit the characteristics of different categories. Also, we have built baseline models that classify the sub-genre based on the mel-spectrograms of a track, achieving strongly competitive results. Besides, we have put forward a few application scenarios of our dataset and baseline model, with a simulated sci-fi tunnel as a short demo built and rendered in a 3D modeling software, with the colors of the lights automated by the output of our model.
翻译:声学分类是音乐技术的基本任务之一。 声学分类的一个主要分支是音乐类的分类。 但是,尽管包含音乐类的多数类型,但现有的音乐类数据集往往没有显示音乐详细次类的精细标记。考虑到混合曲或DJ(现场)集中的歌曲类型的一致性,我们收集并附加了一个家庭音乐数据集,提供4种次类的标签,即未来房屋、低音室、进步住宅和旋律房屋。实验显示,我们的说明很好地展示了不同类别的特征。此外,我们建立了基线模型,根据音轨的螺旋光谱对子类进行分类,取得了很强的竞争性结果。此外,我们还提出了我们数据集和基线模型的几个应用情景,以3D模型软件中制作和制作的模拟的ci-fi隧道为缩影和制成的3D模型,以模型输出自动的光色为基础。