Music genre classification is one of the trending topics in regards to the current Music Information Retrieval (MIR) Research. Since, the dependency of genre is not only limited to the audio profile, we also make use of textual content provided as lyrics of the corresponding song. We implemented a CNN based feature extractor for spectrograms in order to incorporate the acoustic features and a Hierarchical Attention Network based feature extractor for lyrics. We then go on to classify the music track based upon the resulting fused feature vector.

中文翻译：

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基于层次注意和卷积神经网络的新型多峰音乐流派分类器

音乐流派分类是当前音乐信息检索（MIR）研究中的热门话题之一。由于流派的依赖性不仅限于音频配置文件，我们还利用了作为相应歌曲的歌词提供的文本内容。我们为频谱图实现了基于CNN的特征提取器，以便合并声学特征，为歌词实现了基于分层注意力网络的特征提取器。然后，我们根据所得的融合特征向量对音乐曲目进行分类。