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GiantMIDI-Piano: A Large-Scale MIDI Dataset for Classical Piano Music Cover

GiantMIDI-Piano: A Large-Scale MIDI Dataset for Classical Piano Music

Open Access
|May 2022

Figures & Tables

Table 1

Piano MIDI datasets. GP is the abbreviation for GiantMIDI-Piano.

DATASETCOMPOSERSWORKSHOURSTYPE
Piano-midi.de2657137Seq.
Classical Archives13385646Seq.
Kunstderfuge598Seq.
KernScoresSeq.
SUPRA111410Perf.
ASAP16222Perf.
MAESTRO6252984Perf.
MAPS27019Perf.
GiantMIDI-Piano2,78610,8551,23790% Perf.
Curated GP1,7877,23687589% Perf.
tismir-5-1-80-g1.png
Figure 1

Number of solo piano works in the curated GP dataset. Top 100 are shown.

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Figure 2

Duration of solo piano works in the curated GP dataset. Top 100 are shown.

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Figure 3

Distribution of composers’ nationalities for the full GP dataset.

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Figure 4

Pitch distribution of the top 100 composers in the curated GP dataset.

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Figure 5

Note histogram for the curated GP dataset.

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Figure 6

Note histogram for J.S. Bach, Beethoven, and Liszt from the curated GP dataset.

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Figure 7

The number of notes per second of the top 100 composers in the curated GP dataset.

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Figure 8

Pitch class distribution of six composers for the curated GP dataset.

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Figure 9

Interval distribution of six composers for the curated GP dataset.

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Figure 10

Trichord distribution of six composers for the curated GP dataset showing relative (rel.) frequencies of the top six trichords.

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Figure 11

Tetrachord distribution of six composers for the curated GP dataset showing the top six tetrachords.

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Figure 12

Precision, recall, and F1 score of solo piano detection.

Table 2

Accuracy of retrieved music works of six composers.

J. S. BACHMOZARTBEETHOVENCHOPINLISZTDEBUSSY
Correct147858210219729
Incorrect1023570171229
Accuracy59%71%54%37%90%76%
Table 3

Accuracy of retrieved music works of six composers, using the surname constraint.

J. S. BACHMOZARTBEETHOVENCHOPINLISZTDEBUSSY
Correct12972769614127
Incorrect441652163
Accuracy75%82%94%82%96%90%
Table 4

Piano transcription evaluation on the GiantMIDI-Piano dataset.

DISER
Maestro0.0090.0240.0180.061
GiantMIDI-Piano0.0150.0510.0690.154
Relative difference0.0060.0260.0470.094
tismir-5-1-80-g13.png
Figure 13

From left to right: error rate (ER) of 52 solo piano works in the MAESTRO dataset; ER of 52 solo piano works in the GiantMIDI-Piano dataset; relative ER between the MAESTRO and the GiantMIDI-Piano dataset.

DOI: https://doi.org/10.5334/tismir.80 | Journal eISSN: 2514-3298
Language: English
Submitted on: Oct 25, 2020
Accepted on: Feb 1, 2022
Published on: May 12, 2022
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2022 Qiuqiang Kong, Bochen Li, Jitong Chen, Yuxuan Wang, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.