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Dataset for functional harmony recognition
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BPS_FH_Dataset
Taking Form/01
.gitattributes
.gitignore Initial commit Jun 11, 2018
MTL_BLSTM_RNN_Model.py
README.md
STL_BLSTM_RNN_Model.py
preprocessing.py

README.md

Beethoven Piano Sonata with Function Harmony (BPS-FH) dataset

The BPS-FH dataset consists of the symbolic musical data and functional harmony annotations of the 1st movements from Beethoven's 32 piano sonatas. The dataset can be used for functional harmony recognition, and also for symbolic cohrd estimation. More details can be found in the paper:

Tsung-Ping Chen and Li Su, “Functional Harmony Recognition with Multi-task Recurrent Neural Networks,” International Society of Music Information Retrieval Conference (ISMIR), September 2018.

Every piece contins 5 labels, including 1) note events, 2) beats, 3) donw beats, 4) chords, and 5) phrases.

Notes Events

The columns represent onset (in crotchet beats), MIDI note number, morphetic pitch number, duration (in crotchet beats), staff number (integers from zero for the top staff), and measure (-1 for incomplete measure).

Beats and Down Beats

The ontime of beats and down beats.

Chords

The columns represent onset, offset, key, degree, quality, inversion, Roman numeral notation.

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Musical Form

For users who are interested in human analyses of musical form, you are recommended to convert the annotations in the BPS-FH dataset by the parser provided in https://github.com/MarkGotham/Taking-Form.

A converted example is provided in the folder "Taking Form."

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