---
license: cc-by-4.0
task_categories:
- audio-classification
language:
- en
tags:
- music
- piano
- midi
- competition
- ranking
- chopin
pretty_name: Chopin Piano Competition 2015 – Preliminary Round MIDI
size_categories:
- n<1K
---

# Chopin Piano Competition 2015 – Preliminary Round MIDI

Piano MIDI transcriptions of all 130 performers from the **preliminary round** of the
[18th International Chopin Piano Competition (Warsaw, 2015)](https://chopincompetition.pl/en/),
with competition labels for pairwise ranking evaluation.

Companion dataset for the [EVPMR benchmark](https://github.com/anusfoil/eval-piano-midi-repr)
(Evaluation of Piano MIDI Representations).

## Dataset Description

Each performer submitted a ~30-minute recital. Audio was sourced from the official
Chopin Institute YouTube channel and transcribed to MIDI using a piano transcription model.

**Task**: Given two performances, predict which performer advanced further in the competition.
This is a **pairwise ranking** problem (chance accuracy = 0.50).

## Data

```
data/{performer_slug}/{title}.mid     — 130 MIDI files (one per performer)
metadata/splits.csv                   — train/val/test split assignments
metadata/metadata_raw.csv            — per-performer metadata
```

### `metadata/splits.csv`

| Column | Description |
|--------|-------------|
| `midi_path` | Relative path to MIDI file within `data/` |
| `label` | Competition round score (0–4); higher = advanced further |
| `split` | `train` / `val` / `test` |

Split sizes: **90 train / 20 val / 20 test** (stratified by round score, seed=42).

### `metadata/metadata_raw.csv`

| Column | Description |
|--------|-------------|
| `performer_name` | Performer full name |
| `country` | Country code |
| `round_score` | Competition label (0–4) |
| `passed_prelim` | 1 if advanced past preliminary round, else 0 |
| `video_id` | YouTube video ID (source audio) |
| `video_title` | YouTube video title |
| `video_url` | Full YouTube URL |
| `match_score` | Audio-to-MIDI alignment confidence score |

### Round score mapping

| Score | Meaning |
|-------|---------|
| 0 | Did not pass preliminary round |
| 1–4 | Passed preliminary; higher = advanced further in the competition |

## Usage

```python
from evpmr import ChopinCompTask

task = ChopinCompTask()
split = task.load_split(hf_download=True)  # auto-downloads this dataset
```

Or download manually:

```python
from huggingface_hub import snapshot_download
path = snapshot_download("anusfoil/chopin-comp-midi", repo_type="dataset")
# MIDI files at: path/data/{performer_slug}/*.mid
# Splits at:     path/metadata/splits.csv
```

## Baseline Results (EVPMR)

Evaluated with [Aria-medium](https://huggingface.co/loubb/aria-medium-embedding)
(frozen encoder, windowed encoding ~10–15 s per window):

| Probe | Pairwise Accuracy | Antisymmetry |
|-------|:-----------------:|:------------:|
| Linear (binary LogReg on concat embeddings) | 0.562 | 1.000 |
| Attentive (cross-attention, I-JEPA style) | 0.689 | 0.992 |

Chance level = 0.50. Antisymmetry measures consistency: a perfect ranker always
reverses its prediction when the pair is swapped (score = 1.0).

## Provenance & License

- Audio source: [Chopin Institute YouTube channel](https://www.youtube.com/@ChopinInstitute) (CC BY)
- MIDI transcription: automated piano transcription
- Competition results: publicly available from [chopincompetition.pl](https://chopincompetition.pl)

This dataset is released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
Please cite the competition when using this data.