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

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arxiv 2108.01374 v1 pith:HMXF7PUK submitted 2021-08-03 cs.SD cs.MMeess.AS

Hsiao-Tzu Hung , Joann Ching , Seungheon Doh , Nabin Kim , Juhan Nam , Yi-Hsuan Yang This is my paper
classification cs.SDcs.MMeess.AS
keywords musicemotiondatasetemopiagenerationpianousedanalysis
verification ladder T0 review T1 audit T2 compute T3 formal
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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-m\`{o}-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-level emotion labels annotated by four dedicated annotators. Since the clips are not restricted to one clip per song, they can also be used for song-level analysis. We present the methodology for building the dataset, covering the song list curation, clip selection, and emotion annotation processes. Moreover, we prototype use cases on clip-level music emotion classification and emotion-based symbolic music generation by training and evaluating corresponding models using the dataset. The result demonstrates the potential of EMOPIA for being used in future exploration on piano emotion-related MIR tasks.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. AImoclips: A Benchmark for Evaluating Emotion Conveyance in Text-to-Music Generation

    cs.SD 2025-08 conditional novelty 6.0 of 10

    AImoclips is a new open benchmark showing that text-to-music systems convey high-arousal emotions better than low-arousal ones and that all models converge toward emotionally neutral music.

  2. Video-Guided Text-to-Music Generation Using Public Domain Movie Collections

    cs.SD 2025-06 conditional novelty 6.0 of 10

    OSSL is the first self-hosted, mood-annotated video-music dataset, and a video adapter on MusicGen-Medium improves film music generation over text-only baselines.

  3. Workflow-Based Evaluation of Music Generation Systems

    eess.AS 2025-06 conditional novelty 5.0 of 10

    A single-producer workflow evaluation of eight music AI tools finds they work as idea and sound generators but not as complete composers, and proposes a reusable framework.

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