EMOPIA+

EMOPIA+ is a dataset published with paper "Emotion-driven Piano Music Generation via Two-stage Disentanglement and Functional Representation". It is an extension of EMOPIA, a multi-modal (audio and MIDI) database focusing on perceived emotion in pop piano music. To support two-stage generation, we extracted lead sheet (meloly + chord progressions) from original midi files, and manually corrected the key signatures of 367 clips. This dataset comprises 1,071 processed MIDI files along with their event-based representations: functional representation and REMI. For more details about the extraction algorithms and the process to generate events, see the repo EMO-Disentanger. File Description midis/: Processed MIDI clips containing four tracks: Melody, Texture, Bass, and Chord. The first three tracks can be merged into the original MIDI files. adjust_keyname.json: Manually adjusted key signatures. functional/: Functional representations of the MIDI files. performance/: Events for performance, including Melody, Texture and Bass tracks. lead_sheet/: Events for lead sheet, including Melody and Chord tracks. lead_sheet_to_performance/: Events for both lead sheet and performance, facilitating conditional music generation. REMI/: REMI representations of the MIDI files, with the same structure as the functional/. split/: train/val/test splits based on the instructions in EMOPIA. Citation @inproceedings{{EMOPIA}, author = {Hung, Hsiao-Tzu and Ching, Joann and Doh, Seungheon and Kim, Nabin and Nam, Juhan and Yang, Yi-Hsuan}, title = {{EMOPIA}: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation}, booktitle = {Proceedings of the International Society for Music Information Retrieval Conference, {ISMIR}}, year = {2021} }@inproceedings{emodisentanger2024, author = {Jingyue Huang and Ke Chen and Yi-Hsuan Yang}, title = {Emotion-driven Piano Music Generation via Two-stage Disentanglement and Functional Representation}, booktitle = {Proceedings of the International Society for Music Information Retrieval Conference, {ISMIR}}, year = {2024} }