EMOPIA: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation

@article{Hung2021EMOPIAAM,
  title={EMOPIA: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation},
  author={Hsiao-Tzu Hung and Joann Ching and Seungheon Doh and Nabin Kim and Juhan Nam and Yi-Hsuan Yang},
  journal={ArXiv},
  year={2021},
  volume={abs/2108.01374}
}
While there are many music datasets with emotion labels in the literature, they cannot be used for research on symbolic-domain music analysis or generation, as there are usually audio files only. In this paper, we present the EMOPIA (pronounced `yee-mo-pi-uh') dataset, a shared multi-modal (audio and MIDI) database focusing on perceived emotion in pop piano music, to facilitate research on various tasks related to music emotion. The dataset contains 1,087 music clips from 387 songs and clip… 
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