README.md

---
license: cc-by-nc-sa-4.0
task_categories:
- audio-classification
tags:
- music
- piano
- midi
- symbolic-music
- expressive-performance
- score-to-performance
pretty_name: PianoCoRe
size_categories:
- 100K<n<1M
source_datasets:
- extended
- original
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
dataset_info:
  features:
  - name: id
    dtype: string
  - name: composer
    dtype: string
  - name: composition
    dtype: string
  - name: movement
    dtype: string
  - name: performance_id
    dtype: string
  - name: split
    dtype: string
  - name: tier_b
    dtype: bool
  - name: tier_a
    dtype: bool
  - name: tier_a_star
    dtype: bool
  - name: score_dataset
    dtype: string
  - name: score_id
    dtype: string
  - name: score_xml_path
    dtype: string
  - name: score_midi_path
    dtype: string
  - name: score_note_count
    dtype: float32
  - name: score_duration
    dtype: float32
  - name: performance_dataset
    dtype: string
  - name: performance_midi_path
    dtype: string
  - name: performance_note_count
    dtype: float32
  - name: performance_duration
    dtype: float32
  - name: performer
    dtype: string
  - name: is_transcription
    dtype: bool
  - name: capture_model
    dtype: string
  - name: raw_alignment_path
    dtype: string
  - name: raw_recall
    dtype: float32
  - name: raw_precision
    dtype: float32
  - name: raw_adjusted_alignment_ratio
    dtype: float32
  - name: is_duplicate
    dtype: bool
  - name: lead_performance
    dtype: string
  - name: quality_label
    dtype: string
  - name: prob_score
    dtype: float32
  - name: prob_high_quality
    dtype: float32
  - name: prob_low_quality
    dtype: float32
  - name: prob_corrupted
    dtype: float32
  - name: is_refined
    dtype: bool
  - name: refined_score_midi_path
    dtype: string
  - name: refined_score_note_count
    dtype: float32
  - name: refined_score_duration
    dtype: float32
  - name: refined_performance_midi_path
    dtype: string
  - name: refined_performance_note_count
    dtype: float32
  - name: refined_performance_interpolated_note_count
    dtype: float32
  - name: refined_performance_duration
    dtype: float32
  - name: refined_alignment_path
    dtype: string
  - name: refined_recall
    dtype: float32
  - name: score_xml_bytes
    dtype: binary
  - name: score_midi_bytes
    dtype: binary
  - name: performance_midi_bytes
    dtype: binary
  - name: raw_alignment_bytes
    dtype: binary
  - name: refined_score_midi_bytes
    dtype: binary
  - name: refined_performance_midi_bytes
    dtype: binary
  - name: refined_alignment_bytes
    dtype: binary
---


# PianoCoRe: Combined and Refined Piano MIDI Dataset

**PianoCoRe** is a large-scale piano MIDI dataset that unifies and refines major open-source piano corpora. 
It contains **250,046 performances** of **5,625 pieces** written by **483 composers**, totaling **21,763 hours** of performed music. 

**PianoCoRe** provides the most diverse composer- and composition-annotated piano MIDI data.
The metadata includes deduplication flags, MIDI quality labels and precise note-level score-performance alignments. 

The alignments are refined using a **Refined Alignment for Scores and Performances (RAScoP)** pipeline, integrated into the [Symbolic Music Performance modeling (SyMuPe)](https://github.com/ilya16/SyMuPe) Python package. 
The pipeline ensures perfect note-by-note score-performance synchronization for expressive performance modeling.

## Related Resources

*	**TISMIR:** https://doi.org/10.5334/tismir.333
*	**arXiv:** https://arxiv.org/abs/2605.06627
*   **GitHub:** https://github.com/ilya16/PianoCoRe
*	**Zenodo:** https://doi.org/10.5281/zenodo.19186016

**Note**: This Hugging Face version stores data in compressed Parquet files with raw bytes. 
If you prefer the original MIDI files in a directory structure, please use the [Zenodo Mirror](https://doi.org/10.5281/zenodo.19186016).

## Dataset Tiers

| Dataset | Composers | Pieces | Performances | Hours | Scores | Alignments |
| --- | :---: | :---: | :---: | :---: | :---: | :---: |
| **PianoCoRe-C** | 483 | 5,625 | 250,046 | 21,763 | 75.3% | no |
| **PianoCoRe-B** | 478 | 5,591 | 214,092 | 18,757 | 75.0% | no |
| **PianoCoRe-A** | 151 | 1,591 | 157,207 | 12,509 | 100% | note |
| **PianoCoRe-A\*** | 137 | 1,517 | 130,275 | 10,330 | 100% | note |

To support different research applications, the dataset is organized into tiered subsets:

- **PianoCoRe-C (Combined):** a complete mixed-source piano performance collection.

  *Applications*: piano performance analysis, data cleaning algorithms.
- **PianoCoRe-B (Base):** a deduplicated and quality-filtered subset.

  *Applications*: large-scale pre-training, piano performance generation.
- **PianoCoRe-A (Aligned):** a subset containing performances aligned to score.

  *Applications*: score-performance analysis, expressive piano performance rendering.
- **PianoCoRe-A\*:** a high quality subset of the best-quality performances and note-level alignments.

  *Applications*: expressive piano performance rendering, performance-to-score transcription.

## Quick Start

Use the following example code to access the metadata:
```python
from datasets import load_dataset

# Load the train split of the PianoCoRe dataset (streaming mode)
dataset = load_dataset("SyMuPe/PianoCoRe", split="train", streaming=True)

# Optionally drop heavy columns with bytes (e.g., MusicXML/MXL data)
# dataset = dataset.remove_columns(["score_xml_bytes"])

# Filter for high-confidence samples (PianoCoRe-A*)
dataset_a_star = dataset.filter(lambda x: x["tier_a_star"])

# Take one sample
sample = next(iter(dataset_a_star))
print(f"ID: {sample['id']}")  
print(f"Work: {sample['composer']} - {sample['composition']}" + (f" - {sample['movement']}" if sample["movement"] else ""))
print(f"Score: {sample['score_midi_path']}")
print(f"Performance: {sample['performance_midi_path']}\n")
```

The **raw** MIDI data and alignments can be accessed using:
```python
from symusic import Score
from symupe import Alignment

# Load raw score and performance MIDI data
score_midi = Score.from_midi(sample["score_midi_bytes"]) if sample["score_midi_bytes"] is not None else None
performance_midi = Score.from_midi(sample["performance_midi_bytes"])
print(f"Score MIDI: {score_midi}")
print(f"Performance MIDI: {performance_midi}")

# Load raw alignment
if sample['raw_alignment_bytes'] is not None:
    raw_alignment = Alignment.from_bytes(sample["raw_alignment_bytes"])
    print(f"Raw alignment: {len(raw_alignment)} total and {raw_alignment.num_full_pairs} matched pairs")

    # Save in a human-readable format
    # raw_alignment.save("alignment.txt")
```

The **refined** MIDI data and alignments can be accessed using:
```python
import io
import numpy as np
from symusic import Score

if sample["refined_performance_midi_bytes"] is not None:
    # Load refined score and performance MIDI data
    score_midi = Score.from_midi(sample["refined_score_midi_bytes"])
    performance_midi = Score.from_midi(sample["refined_performance_midi_bytes"])
    print(f"Refined Score MIDI: {score_midi}")
    print(f"Refined Performance MIDI: {performance_midi}")

    # Load refined alignment
    refined_alignment = np.load(io.BytesIO(sample["refined_alignment_bytes"]))
    print(f"Refined Alignment:")
    print(f"  performance indices: {refined_alignment['perf_idx']}")
    print(f"  interpolation mask: {refined_alignment['interpolated']}")
```
---

## Dataset Metadata

The **PianoCoRe** metadata rows are organized using a natural sort based on performance MIDI paths. 
The following fields are defined for each entry:

### Core:

- **id** (string): unique sample ID (format: `PianoCoRe_XXXXXX`)
- **composer** (string): name of the composer (format: `[last_name],_[first_name]`)
- **composition** (string): title of the musical work/composition
- **movement** (string, optional): name of the specific movement/part of the composition
- **performance_id** (string): ID of the performance MIDI file, derived from the source dataset name and its internal ID

### Subsets:

- **split** (string): dataset split (`train` or `test`)
- **tier_b** (bool): whether the performance is in the **PianoCoRe-B** subset (deduplicated and quality-filtered)
- **tier_a** (bool):whether the performance is in the **PianoCoRe-A** subset (note-aligned to scores)
- **tier_a_star** (bool): whether the performance is in the **PianoCoRe-A*** subset (highest-confidence alignments)

### Score:

- **score_dataset** (string, optional): source dataset for the score MusicXML/MXL files (ASAP/ATEPP/PDMX/MuseScore)
- **score_id** (string, optional): ID of the score MIDI file, either as in the source dataset or built using the source dataset name and ID
- **score_xml_path** (string, optional): path to the score MusicXML/MXL file within the `raw/` directory
- **score_midi_path** (string, optional): path to the score MIDI file within the `raw/` directory
- **score_note_count** (integer, optional): number of notes in the score MIDI
- **score_duration** (float, optional): duration of the score MIDI in seconds

### Performance:

- **performance_dataset** (string): source dataset of the performance MIDI
- **performance_midi_path** (string): path to the performance MIDI file within the `raw/` directory
- **performance_note_count** (integer): number of notes in the performance MIDI
- **performance_duration** (float): duration of the performance MIDI in seconds
- **performer** (string, optional) name of the pianist (if available)
- **is_transcription** (bool): whether the performance MIDI was transcribed from audio
- **capture_model** (string): hardware (e.g., Yamaha Disklavier) or ML model used to transcribe the MIDI

### Raw alignment:

- **raw_alignment_path** (string, optional): path to the raw `_align.npz` score-performance alignment file within the `raw/` directory, contains indices, pitches and onset for score and performance notes
- **raw_recall** (float, optional): $R_a$, raw alignment recall
- **raw_precision** (float, optional): $P_a$, raw alignment precision
- **raw_adjusted_alignment_ratio** (float, optional): $R'_a$, raw alignment adjusted alignment ratio, defined as $R'_a = \max(P_a, R_a)$

### Deduplication (PianoCoRe-B):

- **is_duplicate** (bool): whether the performance is a near-duplicate of the other performance (`lead_performance`)
- **lead_performance** (string, optional): path to the main (higher priority) version for the duplicate performance MIDI

### Quality labels (PianoCoRe-B):

- **quality_label** (string): MIDI quality label predicted by the classifier ('score', 'high quality', 'low quality' or 'corrupted')
- **prob_score** (float): classifier confidence for Score (S) MIDI quality class
- **prob_high_quality** (float): classifier confidence for High Quality (HQ) MIDI quality class
- **prob_low_quality** (float): classifier confidence for Low Quality (LQ) MIDI quality class
- **prob_corrupted** (float): classifier confidence for Corrupted (C) MIDI quality class

### Refined score, performance and alignment (PianoCoRe-A/A*):

- **is_refined** (bool): whether the performance MIDI was cleaned and refined
- **refined_score_midi_path** (string, optional): path to the refined (single-track) score MIDI file within the `refined/` directory
- **refined_score_note_count** (integer, optional): number of notes in the refined score MIDI
- **refined_score_duration** (float, optional): duration of the refined score MIDI in seconds
- **refined_performance_midi_path** (string, optional): path to the refined (note-by-note aligned) performance MIDI file within the `refined/` directory
- **refined_performance_note_count** (integer, optional): number of notes in the refined performance MIDI
- **refined_performance_interpolated_note_count** (integer, optional): number of synthetic notes added during the interpolation stage
- **refined_performance_duration** (float, optional): duration of the refined performance MIDI in seconds
- **refined_alignment_path** (string, optional): path to the `_refined_align.npz` score-performance alignment file within the `refined/` directory, contains performance indices and boolean interpolation mask
- **refined_recall** (float, optional): $R_{RAScoP}$, refined alignment recall

### Binary data:
- **score_xml_bytes** (binary, optional) raw data for the score MusicXML/MXL file
- **score_midi_bytes** (binary, optional) raw data for the score MIDI file
- **performance_midi_bytes** (binary): raw data for the performance MIDI file
- **raw_alignment_bytes** (binary, optional): raw data for the raw `.npz` alignment file
- **refined_score_midi_bytes** (binary, optional): raw data for the refined score MIDI file
- **refined_performance_midi_bytes** (binary, optional): raw data for the refined performance MIDI file
- **refined_alignment_bytes** (binary, optional): raw data for the refined `.npz` alignment file

---

## Ethical Statement

The curation of large-scale symbolic datasets presents challenges regarding copyright and intellectual property. 
A best-effort attempt was made to filter PianoCoRe according to European Union public-domain regulations (works whose authors have been deceased for more than 70 years). 

## Licensing and Terms of Use

The dataset, original and processed files, metadata, and alignment annotations are published under a **[CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/)** license. 
The license respects the licenses used for the source datasets. The underlying MIDI transcriptions are provided strictly for **non-commercial research and educational purposes**.

## Acknowledgments

PianoCoRe is built upon the invaluable contributions of the open music information retrieval community and existing open-source datasets. 
Acknowledgements and credits are given to the creators of the following source corpora:

| Dataset             | Reference                  | Links                                                                                                                        | License                                                               |
| ------------------- | -------------------------- | ---------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------- |
| **MAESTRO**         | Hawthorne et al. (2019)    | [Paper](https://openreview.net/forum?id=r1lYRjC9F7) / [Dataset](https://magenta.withgoogle.com/datasets/maestro)             | [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) |
| **ASAP**            | Foscarin et al. (2020)     | [Paper](https://archives.ismir.net/ismir2020/paper/000127.pdf) / [Dataset](https://github.com/fosfrancesco/asap-dataset)     | [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) |
| **(n)ASAP**         | Peter et al. (2023)        | [Paper](https://transactions.ismir.net/articles/10.5334/tismir.149) / [Dataset](https://github.com/CPJKU/asap-dataset)       | [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) |
| **ATEPP**           | Zhang et al. (2022)        | [Paper](https://archives.ismir.net/ismir2022/paper/000053.pdf) / [Dataset](https://github.com/tangjjbetsy/ATEPP)             | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)             |
| **GiantMIDI-Piano** | Kong et al. (2022)         | [Paper](https://transactions.ismir.net/articles/10.5334/tismir.80) / [Dataset](https://github.com/bytedance/GiantMIDI-Piano) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)             |
| **Aria-MIDI**       | Bradshaw and Colton (2025) | [Paper](https://openreview.net/forum?id=X5hrhgndxW) / [Dataset](https://github.com/loubbrad/aria-midi)                       | [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) |
| **PERiScoPe**       | Borovik et al. (2025)      | [Paper](https://dl.acm.org/doi/10.1145/3746027.3755871) / [Dataset](https://huggingface.co/datasets/SyMuPe/PERiScoPe)        | [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) |
| **PDMX**            | Long et al. (2025)         | [Paper](https://ieeexplore.ieee.org/document/10890217) / [Dataset](https://github.com/pnlong/PDMX/)                          | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)             |

## Citation

If you use this dataset in your research, please cite:

```bibtex
@article{borovik2026pianocore,
  title={{PianoCoRe: Combined and Refined Piano MIDI Dataset}},
  author={Borovik, Ilya},
  journal={Transactions of the International Society for Music Information Retrieval},
  volume={9},
  number={1},
  pages={144--163},
  year={2026},
  doi={10.5334/tismir.333}
}
```