Emotion4MIDI: a Lyrics-based Emotion-Labeled Symbolic Music Dataset
Serkan Sulun Pedro Oliveira Paula Viana
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.