---
license: other
license_name: mixed-see-description
pretty_name: "MAJEPPA: Piano Performance MIDI with Score Pairings and Expertise Labels"
language:
  - en
size_categories:
  - 1K<n<10K
task_categories:
  - audio-classification
tags:
  - music
  - symbolic-music
  - midi
  - piano
  - performance-analysis
  - music-information-retrieval
  - score-following
  - expertise-assessment
configs:
  - config_name: metadata
    data_files: metadata.parquet
    default: true
  - config_name: alignment
    data_files: alignment.parquet
---

# MAJEPPA

**4,449 solo piano performance MIDI files (279 hours, ~5.0M notes)** transcribed from amateur and professional piano recordings, each labelled with the performer's **expertise level** and **recording context**.

- **4,207 (95%)** paired with a reference score in MIDI — 886 scores covering **880 distinct works and movements** by 52 composers
- **3,862 (87%)** carry a **DTW score↔performance alignment** — 20 million timestamp correspondences
- Every performance links to its **source YouTube recording**

The corpus covers the **full skill spectrum**.

**No audio is distributed.** Symbolic MIDI, metadata, and alignments only.

## Contents

| File | Contents |
|---|---|
| `performance.zip` | `P_0001.mid` … `P_4449.mid` — 4,449 performance transcriptions |
| `score.zip` | `S_0001.mid` … `S_0886.mid` — 886 reference scores |
| `metadata.parquet` | 4,449 rows × 12 columns, one per performance |
| `metadata.csv` | the same table as CSV, for convenience |
| `alignment.parquet` | 20,048,645 rows — DTW warping paths |


### metadata.csv

| Column | Description |
|---|---|
| `performance_id` | `P_NNNN`, file in `performance.zip` |
| `recording_id` | `R_NNNN`, groups clips cut from the same source video |
| `score_id` | `S_NNNN`, file in `score.zip`. Empty when unmatched |
| `composer` | Canonical composer name. Empty for 137 rows |
| `piece_title` | Work title, including movement where applicable |
| `recording_type` | `practice`, `demo_class`, `performance`, `concert_performance`, `sight_read`, `slow_demo`, `fast_demo` |
| `expertise_level` | `piano_teacher`, `adult_beginner`, `adult_intermediate`, `virtuoso`, `child_beginner`, `child_professional` |
| `clip_start_s` | Offset of this clip within its source video |
| `clip_end_s` | End offset. Empty means "to the end of the video", not missing |
| `alignment_cost` | DTW alignment cost |
| `score_coverage` | Fraction of the **score** matched |
| `youtube_url` | Source video (the link might be invalid or removed) |

`performance_id` and `score_id` are **independent ID spaces**. One score serves many performances; use `score_id` for the pairing.

### alignment.parquet

`performance_id`, `score_s`, `perf_s` (float32), in **chronological order**. Each row is one point on the DTW warping path: a score timestamp and the performance timestamp it maps to. Rows are in chronological order. Join to metadata.csv on performance_id.

## Statistics

| | Prac. | Sight. | Perf. | Demo* | Slow | Conc. | **Total** | **Hours** |
|---|---|---|---|---|---|---|---|---|
| Piano teacher | 35 | 15 | 56 | 771 | 329 | 201 | **1,407** | **72.1** |
| Adult beginner | 637 | 404 | 94 | 17 | 3 | 1 | **1,156** | **112.6** |
| Adult intermediate | 464 | 140 | 175 | 22 | 2 | 3 | **806** | **45.7** |
| Child beginner | 188 | 8 | 197 | 5 | 2 | 0 | **400** | **8.9** |
| Child professional | 90 | 0 | 183 | 3 | 0 | 0 | **276** | **13.3** |
| Virtuoso | 0 | 0 | 0 | 0 | 0 | 404 | **404** | **26.7** |
| **Total** | **1,414** | **567** | **705** | **817** | **336** | **609** | **4,449** | **279.3** |

## Ethical considerations

Performances originate from publicly published YouTube videos for research purposes under fair dealing/use. We release only derived MIDI and coarse descriptive tags (expertise and recording context), not raw audio or personally identifying metadata beyond what is already public, and we will respond promptly to any request from an uploader, performer, or rights holder to remove specific content from the dataset. Additionally, we intend the resource for research on performance understanding and music education rather than for replacing teachers or performers. 

## Citation

If you use this dataset, please cite:

```BibTeX
@inproceedings{zhou2026majeppa,
title  = {MAJEPPA: Morphing and Assessing in a Unified Piano Performance Space},
author = {Zhou, Jinwen and Zhang, Huan and Zhai, Weixi and Liang, Jinhua and Hogg, Aidan O. T. and Dixon, Simon},
booktitle = {Proc. International Society for Music Information Retrieval Conference (ISMIR)},
year   = {2026}
}
```

## Contact

jinwen.zhou@qmul.ac.uk