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name string | genre list | chroma array 2D | text string |
|---|---|---|---|
Elvis Costello - Goon Squad | [
"[nan]"
] | [
[
0,
0,
0,
0,
0.6000000238418579,
0,
0,
0.20000000298023224,
0,
0,
0,
0.20000000298023224
],
[
0,
0,
0.6666666865348816,
0,
0.3333333432674408,
0,
0,
0,
0,
0,
0,
0
],
[
0,
0,
0,
0,
0.333333343... | music: Elvis Costello - Goon Squad |
Cosmix - Quietsche-Entchen (feat. Ernie) | [
"[nan]"
] | [
[
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602
],
[
0.083333335816... | music: Cosmix - Quietsche-Entchen (feat. Ernie) |
Basie - All of Me | [
"[nan]"
] | [
[
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602
],
[
0.083333335816... | music: Basie - All of Me |
Green Day - Do Da Da.1 | [
"[nan]"
] | [
[
0,
0,
0,
0,
0.25,
0,
0,
0,
0,
0.75,
0,
0
],
[
0,
0,
0.25,
0,
0.5,
0,
0,
0,
0,
0,
0,
0.25
],
[
0,
0,
0,
0,
0.75,
0,
0,
0,
0,
0,
0,
0.25
],
[
0,
0,
... | music: Green Day - Do Da Da.1 |
Green Day - Coming Clean.2 | [
"[nan]"
] | [
[
0,
0,
0,
0,
0,
0.4000000059604645,
0,
0,
0,
0,
0.5999999642372131,
0
],
[
0,
0,
0.20000000298023224,
0,
0,
0.20000000298023224,
0,
0,
0,
0,
0.5999999642372131,
0
],
[
0,
0,
0.20000000298023224,
... | music: Green Day - Coming Clean.2 |
The Beatles - What You're Doing | [
"[nan]"
] | [
[
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602
],
[
0.083333335816... | music: The Beatles - What You're Doing |
Beatles - I Me Mine | [
"['rock', 'pop']"
] | [
[
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602
],
[
0.083333335816... | music: Beatles - I Me Mine |
Darts - Duke of Earl | [
"[nan]"
] | [
[
0,
0,
0,
0.6000000238418579,
0,
0,
0,
0.20000000298023224,
0,
0,
0.20000000298023224,
0
],
[
0,
0,
0,
0.6000000238418579,
0,
0,
0,
0.20000000298023224,
0,
0,
0.20000000298023224,
0
],
[
0.6000000238418579,
... | music: Darts - Duke of Earl |
Isley Brothers - Shout | [
"['funk', 'rock', 'rnb-soul', 'christian-gospel']"
] | [
[
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0
],
[
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0
],
[
0.5,
0,
0.5,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
[
1,
0,
0,
0,
0,... | music: Isley Brothers - Shout |
Creedence Clearwater Revival - Have You Ever Seen the Rain | [
"[nan]"
] | [
[
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602
],
[
0.083333335816... | music: Creedence Clearwater Revival - Have You Ever Seen the Rain |
Ciani, Suzanne Mozart | [
"['lyrics', 'rate']"
] | [
[
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
[
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
[
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0
],
[
0,
0,
0,
0,
1,
... | music: Ciani, Suzanne Mozart |
Louis Armstrong - (What a) Wonderful World.5 | [
"[nan]"
] | [
[
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602
],
[
0.083333335816... | music: Louis Armstrong - (What a) Wonderful World.5 |
Drafi Deutscher - Shake Hands | [
"[nan]"
] | [
[
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602
],
[
0.083333335816... | music: Drafi Deutscher - Shake Hands |
Francis Connie - Stupid Cupid | [
"[nan]"
] | [
[
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602
],
[
0.083333335816... | music: Francis Connie - Stupid Cupid |
Alpert - South of the Border | [
"[nan]"
] | [
[
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602,
0.0833333358168602
],
[
0.083333335816... | music: Alpert - South of the Border |
End of preview.
MIDI Chroma Dataset
This version requires the genres to be fixed and a restructure before it's compatible with training.
Pre-processed version of foldl/midi with chroma features extracted directly from MIDI note events.
Dataset Description
This dataset contains 4719 songs with pre-computed chroma features for efficient music generation training.
Features
- name: Song title (string)
- genre: List of genres (list of strings)
- chroma: Pre-computed chroma features
[128, 12](float32 array)- 12 pitch classes (C, C#, D, D#, E, F, F#, G, G#, A, A#, B)
- 128 time steps
- Values normalized to sum to 1.0 per timestep
- text: Text description for conditioning (string)
Extraction Method
Chroma features are extracted directly from MIDI note events without audio synthesis:
- Notes are mapped to their pitch class (0-11)
- Velocity is used for intensity weighting
- Temporal resolution: ~10 FPS
- Much faster than audio-based extraction
Usage
from datasets import load_dataset
import torch
# Load dataset
dataset = load_dataset("AbstractPhil/foldl-midi")
# Access samples
sample = dataset['train'][0]
chroma = torch.tensor(sample['chroma']) # [128, 12]
text = sample['text'] # "rock, pop: Genesis - The Light Dies Down"
print(f"Text: {text}")
print(f"Chroma shape: {chroma.shape}")
Training ChromaLyra
This dataset is designed for training ChromaLyra, a geometric VAE for music generation:
from geovocab2.train.model.chroma.chroma_lyra import ChromaLyra, ChromaLyraConfig
config = ChromaLyraConfig(
n_chroma=12,
seq_len=128,
latent_dim=256,
hidden_dim=384
)
model = ChromaLyra(config)
# Train with text conditioning...
Dataset Creation
Created by extracting chroma from valid MIDI files in foldl/midi dataset:
- Filtered songs: 1s - 3min duration
- Skipped empty/drum-only tracks
- Original: ~20K MIDI files → This dataset: ~4719 valid samples
Citation
Original dataset:
@misc{foldl-midi,
author = {foldl},
title = {MIDI Dataset},
year = {2023},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/foldl/midi}
}
Geometric approach:
@misc{abstract-phil-geovocab,
author = {AbstractPhil},
title = {GeoVocab: Geometric Deep Learning for Music Generation},
year = {2025},
url = {https://github.com/AbstractPhil/geovocab2}
}
License
Same as original foldl/midi dataset; https://huggingface.co/datasets/foldl/midi
Acknowledgments
- Original MIDI dataset: foldl
- Chroma extraction: pretty_midi library
- Geometric VAE architecture: AbstractPhil/GeoVocab2
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