We present a new large-scale emotion-labeled symbolic music dataset
consisting of 12k MIDI songs. To create this dataset, we first trained emotion
classification models on the GoEmotions dataset, achieving state-of-the-art
results with a model half the size of the baseline. We then applied these
models to lyrics from two large-scale MIDI datasets. Our dataset covers a wide
range of fine-grained emotions, providing a valuable resource to explore the
connection between music and emotions and, especially, to develop models that
can generate music based on specific emotions. Our code for inference, trained
models, and datasets are available online.

我们提出了一个新的大规模情感标记的符号音乐数据集，该数据集包括 12k 首 MIDI 音乐。通过在 GoEmotions 数据集上训练情感分类模型，我们实现了半基线模型大小的先进结果。然后，我们将这些模型应用到两个大规模 MIDI 数据集的歌词上。我们的数据集涵盖了广泛的细粒度情感，为探究音乐与情感之间的联系以及基于特定情感生成音乐的模型的发展提供了宝贵的资源。我们的推断代码、训练模型和数据集在网上可获得。