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Update to 2511 performances with full metadata + README

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  1. README.md +19 -23
README.md CHANGED
@@ -3,43 +3,39 @@ license: cc-by-4.0
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  task_categories:
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  - audio-classification
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  tags:
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- - music
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  - piano
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  - midi
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- - performance-quality
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- - regression
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- pretty_name: YCU-PPE-III Piano MIDI (Transcribed)
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  size_categories:
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- - n<1K
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  ---
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  # YCU-PPE-III: Piano Performance MIDI Dataset
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- MIDI transcriptions of the YCU-PPE-III piano performance dataset (Wang et al.),
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- used for **unreferenced Performance MOS (PMOS) prediction** in [EVPMR](https://github.com/anusfoil/eval-piano-midi-repr).
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  ## Overview
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- - **606 MIDI files** transcribed from WAV recordings via transkun
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  - **13 songs** performed by student pianists
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- - **Labels**: normalized instructor ratings (0-1 scale, originally 1.5-5.0)
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- - **Splits**: 424 train / 91 val / 91 test (stratified)
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-
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- ## Task
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-
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- Regression: given a piano performance MIDI (without reference score),
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- predict a quality rating. Metrics: MSE, MAE, Pearson r, Spearman rho.
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-
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- ## Directory Structure
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-
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- ## Usage with EVPMR
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- ## Source
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- - Original audio dataset: YCU-PPE-III (Wang et al.)
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- - Transcription: transkun (automatic piano transcription)
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- - Part of [EVPMR](https://github.com/anusfoil/eval-piano-midi-repr) benchmark
 
 
 
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  task_categories:
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  - audio-classification
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  tags:
 
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  - piano
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  - midi
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+ - performance-assessment
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+ - music
 
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  size_categories:
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+ - 1K<n<10K
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  ---
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  # YCU-PPE-III: Piano Performance MIDI Dataset
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+ MIDI transcriptions of the YCU-PPE-III piano performance dataset (Wang et al.), used for **unreferenced Performance MOS (PMOS) prediction** in [EVPMR](https://github.com/anusfoil/eval-piano-midi-repr).
 
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  ## Overview
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+ - **2,627 MIDI files** transcribed from WAV recordings via [transkun](https://github.com/RongTongZi/transkun)
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  - **13 songs** performed by student pianists
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+ - **2,511 performances** with ratings from 3 expert judges (0-100 scale each)
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+ - **Labels**: normalized mean score to [0, 1]
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+ - **Splits**: 1,757 train / 377 val / 377 test (stratified by song)
 
 
 
 
 
 
 
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+ ## Metadata
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+ `metadata/metadata.csv` columns: midi_path, name, song_id, piece_cn, piece_en, judge_1, judge_2, judge_3, mean_score, label, split
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+ ## Task
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+ Regression: given a piano performance MIDI (without reference score), predict a quality rating.
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+ Metrics: MSE, MAE, Pearson r, Spearman rho.
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+ ## Directory Structure
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+ ```
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+ data/{song_id}/{name}.mid # 2,627 MIDI files
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+ metadata/splits.csv # 2,511 entries: midi_path, label, split
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+ metadata/metadata.csv # Full metadata with judge scores + piece names
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+ ```