Music genre classification utilizing neural networks (NNs) has achieved some limited success in recent years. Differences in song libraries, machine learning techniques, input formats, and types of NNs implemented have all had varying levels of success. This article reviews some of the machine learning techniques utilized in this area. It also presents research work on music genre classification. The research uses images of spectrograms generated from timeslices of songs as the input into an NN to classify the songs into their respective musical genres.

中文翻译：

---

神经网络音乐流派分类

近年来，利用神经网络 (NN) 进行的音乐流派分类取得了一些有限的成功。歌曲库、机器学习技术、输入格式和所实现的神经网络类型的差异都取得了不同程度的成功。本文回顾了该领域中使用的一些机器学习技术。它还介绍了音乐流派分类的研究工作。该研究使用从歌曲时间片生成的频谱图图像作为神经网络的输入，将歌曲分类为各自的音乐流派。