audio
audioduration (s) 4
4
| root_note_name
stringclasses 4
values | chord_type
stringclasses 4
values | inversion
int64 5
64
| root_note_is_accidental
bool 2
classes | root_note_pitch_class
int64 0
3
| midi_program_num
int64 0
111
| midi_program_name
stringclasses 92
values | midi_category
stringclasses 13
values |
---|---|---|---|---|---|---|---|---|
C | major | 5 | false | 0 | 0 | Acoustic Grand Piano | Piano Timbres |
|
C | major | 5 | false | 0 | 1 | Bright Acoustic Piano | Piano Timbres |
|
C | major | 5 | false | 0 | 2 | Electric Grand Piano | Piano Timbres |
|
C | major | 5 | false | 0 | 3 | Honky-tonk Piano | Piano Timbres |
|
C | major | 5 | false | 0 | 4 | Rhodes Piano | Piano Timbres |
|
C | major | 5 | false | 0 | 5 | Chorused Piano | Piano Timbres |
|
C | major | 5 | false | 0 | 6 | Harpsichord | Piano Timbres |
|
C | major | 5 | false | 0 | 7 | Clavinet | Piano Timbres |
|
C | major | 5 | false | 0 | 10 | Music Box | Chromatic Percussion |
|
C | major | 5 | false | 0 | 11 | Vibraphone | Chromatic Percussion |
|
C | major | 5 | false | 0 | 12 | Marimba | Chromatic Percussion |
|
C | major | 5 | false | 0 | 13 | Xylophone | Chromatic Percussion |
|
C | major | 5 | false | 0 | 15 | Dulcimer | Chromatic Percussion |
|
C | major | 5 | false | 0 | 16 | Hammond Organ | Organ Timbres |
|
C | major | 5 | false | 0 | 17 | Percussive Organ | Organ Timbres |
|
C | major | 5 | false | 0 | 18 | Rock Organ | Organ Timbres |
|
C | major | 5 | false | 0 | 19 | Church Organ | Organ Timbres |
|
C | major | 5 | false | 0 | 20 | Reed Organ | Organ Timbres |
|
C | major | 5 | false | 0 | 24 | Acoustic Nylon Guitar | Guitar Timbres |
|
C | major | 5 | false | 0 | 25 | Acoustic Steel Guitar | Guitar Timbres |
|
C | major | 5 | false | 0 | 26 | Electric Jazz Guitar | Guitar Timbres |
|
C | major | 5 | false | 0 | 27 | Electric Clean Guitar | Guitar Timbres |
|
C | major | 5 | false | 0 | 28 | Electric Muted Guitar | Guitar Timbres |
|
C | major | 5 | false | 0 | 29 | Overdriven Guitar | Guitar Timbres |
|
C | major | 5 | false | 0 | 30 | Distortion Guitar | Guitar Timbres |
|
C | major | 5 | false | 0 | 32 | Acoustic Bass | Bass Timbres |
|
C | major | 5 | false | 0 | 33 | Fingered Electric Bass | Bass Timbres |
|
C | major | 5 | false | 0 | 34 | Plucked Electric Bass | Bass Timbres |
|
C | major | 5 | false | 0 | 35 | Fretless Bass | Bass Timbres |
|
C | major | 5 | false | 0 | 36 | Slap Bass 1 | Bass Timbres |
|
C | major | 5 | false | 0 | 37 | Slap Bass 2 | Bass Timbres |
|
C | major | 5 | false | 0 | 38 | Synth Bass 1 | Bass Timbres |
|
C | major | 5 | false | 0 | 39 | Synth Bass 2 | Bass Timbres |
|
C | major | 5 | false | 0 | 40 | Violin | String Timbres |
|
C | major | 5 | false | 0 | 41 | Viola | String Timbres |
|
C | major | 5 | false | 0 | 42 | Cello | String Timbres |
|
C | major | 5 | false | 0 | 43 | Contrabass | String Timbres |
|
C | major | 5 | false | 0 | 44 | Tremolo Strings | String Timbres |
|
C | major | 5 | false | 0 | 45 | Pizzicato Strings | String Timbres |
|
C | major | 5 | false | 0 | 46 | Orchestral Harp | String Timbres |
|
C | major | 5 | false | 0 | 48 | String Ensemble 1 | Ensemble Timbres |
|
C | major | 5 | false | 0 | 49 | String Ensemble 2 | Ensemble Timbres |
|
C | major | 5 | false | 0 | 50 | Synth Strings 1 | Ensemble Timbres |
|
C | major | 5 | false | 0 | 51 | Synth Strings 2 | Ensemble Timbres |
|
C | major | 5 | false | 0 | 52 | Choir "Aah" | Ensemble Timbres |
|
C | major | 5 | false | 0 | 53 | Choir "Ooh" | Ensemble Timbres |
|
C | major | 5 | false | 0 | 54 | Synth Voice | Ensemble Timbres |
|
C | major | 5 | false | 0 | 56 | Trumpet | Brass Timbres |
|
C | major | 5 | false | 0 | 57 | Trombone | Brass Timbres |
|
C | major | 5 | false | 0 | 58 | Tuba | Brass Timbres |
|
C | major | 5 | false | 0 | 59 | Muted Trumpet | Brass Timbres |
|
C | major | 5 | false | 0 | 60 | French Horn | Brass Timbres |
|
C | major | 5 | false | 0 | 61 | Brass Section | Brass Timbres |
|
C | major | 5 | false | 0 | 62 | Synth Brass 1 | Brass Timbres |
|
C | major | 5 | false | 0 | 63 | Synth Brass 2 | Brass Timbres |
|
C | major | 5 | false | 0 | 64 | Soprano Sax | Reed Timbres |
|
C | major | 5 | false | 0 | 65 | Alto Sax | Reed Timbres |
|
C | major | 5 | false | 0 | 66 | Tenor Sax | Reed Timbres |
|
C | major | 5 | false | 0 | 67 | Baritone Sax | Reed Timbres |
|
C | major | 5 | false | 0 | 68 | Oboe | Reed Timbres |
|
C | major | 5 | false | 0 | 69 | English Horn | Reed Timbres |
|
C | major | 5 | false | 0 | 70 | Bassoon | Reed Timbres |
|
C | major | 5 | false | 0 | 71 | Clarinet | Reed Timbres |
|
C | major | 5 | false | 0 | 72 | Piccolo | Pipe Timbres |
|
C | major | 5 | false | 0 | 73 | Flute | Pipe Timbres |
|
C | major | 5 | false | 0 | 74 | Recorder | Pipe Timbres |
|
C | major | 5 | false | 0 | 75 | Pan Flute | Pipe Timbres |
|
C | major | 5 | false | 0 | 76 | Bottle Blow | Pipe Timbres |
|
C | major | 5 | false | 0 | 79 | Ocarina | Pipe Timbres |
|
C | major | 5 | false | 0 | 80 | Square Wave Lead | Synth Lead |
|
C | major | 5 | false | 0 | 81 | Sawtooth Wave Lead | Synth Lead |
|
C | major | 5 | false | 0 | 82 | Calliope Lead | Synth Lead |
|
C | major | 5 | false | 0 | 83 | Chiff Lead | Synth Lead |
|
C | major | 5 | false | 0 | 84 | Charang Lead | Synth Lead |
|
C | major | 5 | false | 0 | 85 | Voice Lead | Synth Lead |
|
C | major | 5 | false | 0 | 87 | Bass Lead | Synth Lead |
|
C | major | 5 | false | 0 | 88 | New Age Pad | Synth Pad |
|
C | major | 5 | false | 0 | 89 | Warm Pad | Synth Pad |
|
C | major | 5 | false | 0 | 90 | Polysynth Pad | Synth Pad |
|
C | major | 5 | false | 0 | 91 | Choir Pad | Synth Pad |
|
C | major | 5 | false | 0 | 92 | Bowed Pad | Synth Pad |
|
C | major | 5 | false | 0 | 93 | Metallic Pad | Synth Pad |
|
C | major | 5 | false | 0 | 94 | Halo Pad | Synth Pad |
|
C | major | 5 | false | 0 | 95 | Sweep Pad | Synth Pad |
|
C | major | 5 | false | 0 | 104 | Sitar | Ethnic Timbres |
|
C | major | 5 | false | 0 | 105 | Banjo | Ethnic Timbres |
|
C | major | 5 | false | 0 | 106 | Shamisen | Ethnic Timbres |
|
C | major | 5 | false | 0 | 107 | Koto | Ethnic Timbres |
|
C | major | 5 | false | 0 | 108 | Kalimba | Ethnic Timbres |
|
C | major | 5 | false | 0 | 109 | Bagpipe | Ethnic Timbres |
|
C | major | 5 | false | 0 | 110 | Fiddle | Ethnic Timbres |
|
C | major | 5 | false | 0 | 111 | Shanai | Ethnic Timbres |
|
C | major | 6 | false | 0 | 0 | Acoustic Grand Piano | Piano Timbres |
|
C | major | 6 | false | 0 | 1 | Bright Acoustic Piano | Piano Timbres |
|
C | major | 6 | false | 0 | 2 | Electric Grand Piano | Piano Timbres |
|
C | major | 6 | false | 0 | 3 | Honky-tonk Piano | Piano Timbres |
|
C | major | 6 | false | 0 | 4 | Rhodes Piano | Piano Timbres |
|
C | major | 6 | false | 0 | 5 | Chorused Piano | Piano Timbres |
|
C | major | 6 | false | 0 | 6 | Harpsichord | Piano Timbres |
|
C | major | 6 | false | 0 | 7 | Clavinet | Piano Timbres |
Dataset Card for SynTheory
Dataset Summary
SynTheory is a synthetic dataset of music theory concepts, specifically rhythmic (tempos and time signatures) and tonal (notes, intervals, scales, chords, and chord progressions).
Each of these 7 concepts has its own config.
tempos
consist of 161 total integer tempos (bpm
) ranging from 50 BPM to 210 BPM (inclusive), 5 percussive instrument types (click_config_name
), and 5 random start time offsets (offset_time
).
time_signatures
consist of 8 time signatures (time_signature
), 5 percussive instrument types (click_config_name
), 10 random start time offsets (offset_time
), and 3 reverb levels (reverb_level
). The 8 time signatures are 2/2, 2/4, 3/4, 3/8, 4/4, 6/8, 9/8, and 12/8.
notes
consist of 12 pitch classes (root_note_name
), 9 octaves (octave
), and 92 instrument types (midi_program_name
). The 12 pitch classes are C, C#, D, D#, E, F, F#, G, G#, A, A# and B.
intervals
consist of 12 interval sizes (interval
), 12 root notes (root_note_name
), 92 instrument types (midi_program_name
), and 3 play styles (play_style_name
). The 12 intervals are minor 2nd, Major 2nd, minor 3rd, Major 3rd, Perfect 4th, Tritone, Perfect 5th, minor 6th, Major 6th, minor 7th, Major 7th, and Perfect octave.
scales
consist of 7 modes (mode
), 12 root notes (root_note_name
), 92 instrument types (midi_program_name
), and 2 play styles (play_style_name
). The 7 modes are Ionian, Dorian, Phrygian, Lydian, Mixolydian, Aeolian, and Locrian.
chords
consist of 4 chord quality (chord_type
), 3 inversions (inversion
), 12 root notes (root_note_name
), and 92 instrument types (midi_program_name
). The 4 chord quality types are major, minor, augmented, and diminished. The 3 inversions are root position, first inversion, and second inversion.
simple_progressions
consist of 19 chord progressions (chord_progression
), 12 root notes (key_note_name
), and 92 instrument types (midi_program_name
). The 19 chord progressions consist of 10 chord progressions in major mode and 9 in natural minor mode. The major mode chord progressions are (I–IV–V–I), (I–IV–vi–V), (I–V–vi–IV), (I–vi–IV–V), (ii–V–I–Vi), (IV–I–V–Vi), (IV–V–iii–Vi), (V–IV–I–V), (V–vi–IV–I), and (vi–IV–I–V). The natural minor mode chord progressions are (i–ii◦–v–i), (i–III–iv–i), (i–iv–v–i), (i–VI–III–VII), (i–VI–VII–i), (i–VI–VII–III), (i–VII–VI–IV), (iv–VII–i–i), and (VII–vi–VII–i).
Supported Tasks and Leaderboards
audio-classification
: This can be used towards music theory classification tasks.feature-extraction
: Our samples can be fed into pretrained audio codecs to extract representations from the model, which can be further used for downstream MIR tasks.
How to use
The datasets
library allows you to load and pre-process your dataset in pure Python, at scale. The dataset can be downloaded and prepared in one call to your local drive by using the load_dataset
function.
For example, to download the notes config, simply specify the corresponding language config name (i.e., "notes"):
from datasets import load_dataset
notes = load_dataset("meganwei/syntheory", "notes")
Using the datasets library, you can also stream the dataset on-the-fly by adding a streaming=True
argument to the load_dataset
function call. Loading a dataset in streaming mode loads individual samples of the dataset at a time, rather than downloading the entire dataset to disk.
from datasets import load_dataset
notes = load_dataset("meganwei/syntheory", "notes", streaming=True)
print(next(iter(notes)))
Bonus: create a PyTorch dataloader directly with your own datasets (local/streamed).
Local:
from datasets import load_dataset
from torch.utils.data.sampler import BatchSampler, RandomSampler
from torch.utils.data import DataLoader
notes = load_dataset("meganwei/syntheory", "notes")
batch_sampler = BatchSampler(RandomSampler(notes), batch_size=32, drop_last=False)
dataloader = DataLoader(notes, batch_sampler=batch_sampler)
Streaming:
from datasets import load_dataset
from torch.utils.data import DataLoader
notes = load_dataset("meganwei/syntheory", "notes", streaming=True)
dataloader = DataLoader(notes, batch_size=32)
To find out more about loading and preparing audio datasets, head over to hf.co/blog/audio-datasets.
Example scripts
[More Information Needed]
Dataset Structure
Data Fields
[More Information Needed]
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
For the notes music theory concept, there are 9,936 distinct note configurations. However, our dataset contains 9,848 non-silent samples. The 88 silent samples at extreme registers are unvoiceable with our soundfont. With a more complete soundfont, all 9,936 configurations are realizable to audio.
The silent samples are the following audio files: 0_0_C_10_Music_Box.wav, 0_0_C_56_Trumpet.wav, 0_0_C_68_Oboe.wav, 1_0_C#_10_Music_Box.wav, 1_0_C#_56_Trumpet.wav, 1_0_C#_68_Oboe.wav, 2_0_D_10_Music_Box.wav, 2_0_D_56_Trumpet.wav, 2_0_D_68_Oboe.wav, 3_0_D#_10_Music_Box.wav, 3_0_D#_56_Trumpet.wav, 3_0_D#_68_Oboe.wav, 4_0_E_10_Music_Box.wav, 4_0_E_56_Trumpet.wav, 4_0_E_68_Oboe.wav, 5_0_F_10_Music_Box.wav, 5_0_F_56_Trumpet.wav, 5_0_F_68_Oboe.wav, 6_0_F#_10_Music_Box.wav, 6_0_F#_56_Trumpet.wav, 6_0_F#_68_Oboe.wav, 7_0_G_10_Music_Box.wav, 7_0_G_56_Trumpet.wav, 7_0_G_68_Oboe.wav, 8_0_G#_10_Music_Box.wav, 8_0_G#_56_Trumpet.wav, 8_0_G#_68_Oboe.wav, 9_0_A_10_Music_Box.wav, 9_0_A_56_Trumpet.wav, 9_0_A_68_Oboe.wav, 10_0_A#_10_Music_Box.wav, 10_0_A#_56_Trumpet.wav, 10_0_A#_68_Oboe.wav, 11_0_B_10_Music_Box.wav, 11_0_B_56_Trumpet.wav, 11_0_B_68_Oboe.wav, 12_0_C_68_Oboe.wav, 13_0_C#_68_Oboe.wav, 14_0_D_68_Oboe.wav, 15_0_D#_68_Oboe.wav, 16_0_E_68_Oboe.wav, 17_0_F_68_Oboe.wav, 18_0_F#_68_Oboe.wav, 19_0_G_68_Oboe.wav, 20_0_G#_68_Oboe.wav, 21_0_A_68_Oboe.wav, 22_0_A#_68_Oboe.wav, 23_0_B_68_Oboe.wav, 24_0_C_68_Oboe.wav, 25_0_C#_68_Oboe.wav, 26_0_D_68_Oboe.wav, 27_0_D#_68_Oboe.wav, 28_0_E_68_Oboe.wav, 29_0_F_68_Oboe.wav, 30_0_F#_68_Oboe.wav, 31_0_G_68_Oboe.wav, 32_0_G#_68_Oboe.wav, 33_0_A_68_Oboe.wav, 34_0_A#_68_Oboe.wav, 35_0_B_68_Oboe.wav, 80_2_G#_67_Baritone_Sax.wav, 81_2_A_67_Baritone_Sax.wav, 82_2_A#_67_Baritone_Sax.wav, 83_2_B_67_Baritone_Sax.wav, 84_2_C_67_Baritone_Sax.wav, 85_2_C#_67_Baritone_Sax.wav, 86_2_D_67_Baritone_Sax.wav, 87_2_D#_67_Baritone_Sax.wav, 88_2_E_67_Baritone_Sax.wav, 89_2_F_67_Baritone_Sax.wav, 90_2_F#_67_Baritone_Sax.wav, 91_2_G_67_Baritone_Sax.wav, 92_2_G#_67_Baritone_Sax.wav, 93_2_A_67_Baritone_Sax.wav, 94_2_A#_67_Baritone_Sax.wav, 95_2_B_67_Baritone_Sax.wav, 96_2_C_67_Baritone_Sax.wav, 97_2_C#_67_Baritone_Sax.wav, 98_2_D_67_Baritone_Sax.wav, 99_2_D#_67_Baritone_Sax.wav, 100_2_E_67_Baritone_Sax.wav, 101_2_F_67_Baritone_Sax.wav, 102_2_F#_67_Baritone_Sax.wav, 103_2_G_67_Baritone_Sax.wav, 104_2_G#_67_Baritone_Sax.wav, 105_2_A_67_Baritone_Sax.wav, 106_2_A#_67_Baritone_Sax.wav, and 107_2_B_67_Baritone_Sax.wav.
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
@inproceedings{Wei2024-music,
title={Do Music Generation Models Encode Music Theory?},
author={Wei, Megan and Freeman, Michael and Donahue, Chris and Sun, Chen},
booktitle={International Society for Music Information Retrieval},
year={2024}
}
Data Statistics
Concept | Number of Samples |
---|---|
Tempo | 4,025 |
Time Signatures | 1,200 |
Notes | 9,936 |
Intervals | 39,744 |
Scales | 15,456 |
Chords | 13,248 |
Chord Progressions | 20,976 |
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