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

arXiv: https://arxiv.org/abs/2108.01374 · HTML: https://mlsanity.com/paper/2108.01374/

## Key facts

- Cited by 53 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Aug 2021.

## Built on by (most cited first, 30 of 53)

- [MuseCoco: Generating Symbolic Music from Text](https://mlsanity.com/paper/2306.00110/) (2023)
- [Byte Pair Encoding for Symbolic Music](https://mlsanity.com/paper/2301.11975/) (2023)
- [PDMX: A Large-Scale Public Domain MusicXML Dataset for Symbolic Music Processing](https://mlsanity.com/paper/2409.10831/) (2024)
- [Symbolic music generation conditioned on continuous-valued emotions](https://mlsanity.com/paper/2203.16165/) (2022)
- [PianoBART: Symbolic Piano Music Generation and Understanding with Large-Scale Pre-Training](https://mlsanity.com/paper/2407.03361/) (2024)
- [Controlling Perceived Emotion in Symbolic Music Generation with Monte Carlo Tree Search](https://mlsanity.com/paper/2208.05162/) (2022)
- [Generating music with sentiment using Transformer-GANs](https://mlsanity.com/paper/2212.11134/) (2022)
- [Natural Language Processing Methods for Symbolic Music Generation and Information Retrieval: a Survey](https://mlsanity.com/paper/2402.17467/) (2024)
- [WildScore: Benchmarking MLLMs in-the-Wild Symbolic Music Reasoning](https://mlsanity.com/paper/2509.04744/) (2025)
- [AI-Based Affective Music Generation Systems: A Review of Methods, and Challenges](https://mlsanity.com/paper/2301.06890/) (2023)
- [Composer Style-specific Symbolic Music Generation Using Vector Quantized Discrete Diffusion Models](https://mlsanity.com/paper/2310.14044/) (2023)
- [ComMU: Dataset for Combinatorial Music Generation](https://mlsanity.com/paper/2211.09385/) (2022)
- [Conditional Drums Generation using Compound Word Representations](https://mlsanity.com/paper/2202.04464/) (2022)
- [YM2413-MDB: A Multi-Instrumental FM Video Game Music Dataset with Emotion Annotations](https://mlsanity.com/paper/2211.07131/) (2022)
- [Are We There Yet? A Brief Survey of Music Emotion Prediction Datasets, Models and Outstanding Challenges](https://mlsanity.com/paper/2406.08809/) (2024)
- [Towards Unified Music Emotion Recognition across Dimensional and Categorical Models](https://mlsanity.com/paper/2502.03979/) (2025)
- [The GigaMIDI Dataset with Features for Expressive Music Performance Detection](https://mlsanity.com/paper/2502.17726/) (2025)
- [Impact of time and note duration tokenizations on deep learning symbolic music modeling](https://mlsanity.com/paper/2310.08497/) (2023)
- [ABC-Eval: Benchmarking Large Language Models on Symbolic Music Understanding and Instruction Following](https://mlsanity.com/paper/2509.23350/) (2025)
- [REMAST: Real-time Emotion-based Music Arrangement with Soft Transition](https://mlsanity.com/paper/2305.08029/) (2023)
- [EmoGen: Eliminating Subjective Bias in Emotional Music Generation](https://mlsanity.com/paper/2307.01229/) (2023)
- [N-Gram Unsupervised Compoundation and Feature Injection for Better Symbolic Music Understanding](https://mlsanity.com/paper/2312.08931/) (2023)
- [Let Network Decide What to Learn: Symbolic Music Understanding Model Based on Large-scale Adversarial Pre-training](https://mlsanity.com/paper/2407.08306/) (2024)
- [Emotion-driven Piano Music Generation via Two-stage Disentanglement and Functional Representation](https://mlsanity.com/paper/2407.20955/) (2024)
- [Affective Visual Dialog: A Large-Scale Benchmark for Emotional Reasoning Based on Visually Grounded Conversations](https://mlsanity.com/paper/2308.16349/) (2023)
- [Emotion-Driven Melody Harmonization via Melodic Variation and Functional Representation](https://mlsanity.com/paper/2407.20176/) (2024)
- [A Survey on Music Generation from Single-Modal, Cross-Modal, and Multi-Modal Perspectives](https://mlsanity.com/paper/2504.00837/) (2025)
- [Moonbeam: A MIDI Foundation Model Using Both Absolute and Relative Music Attributes](https://mlsanity.com/paper/2505.15559/) (2025)
- [A Novel Multi-Task Learning Method for Symbolic Music Emotion Recognition](https://mlsanity.com/paper/2201.05782/) (2022)
- [IteraTTA: An interface for exploring both text prompts and audio priors in generating music with text-to-audio models](https://mlsanity.com/paper/2307.13005/) (2023)

## Abstract (arXiv)

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.