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Bach Choral Harmony Data Set
Download: Data Folder, Data Set Description

Abstract: The data set is composed of 60 chorales (5665 events) by J.S. Bach (1675-1750). Each event of each chorale is labelled using 1 among 101 chord labels and described through 14 features.

Data Set Characteristics:  

Sequential

Number of Instances:

5665

Area:

N/A

Attribute Characteristics:

N/A

Number of Attributes:

17

Date Donated

2014-05-20

Associated Tasks:

Classification

Missing Values?

N/A

Number of Web Hits:

27387


Source:

-- Creators: Daniele P. Radicioni and Roberto Esposito
-- Donor: Daniele P. Radicioni (radicion '@' di.unito.it) and Roberto Esposito (esposito '@' di.unito.it)
-- Date: May, 2014


Data Set Information:

Pitch classes information has been extracted from MIDI sources downloaded
from (JSB Chorales)[[Web Link]]. Meter information has
been computed through the Meter program which is part of the Melisma
music analyser (Melisma)[[Web Link]].
Chord labels have been manually annotated by a human expert.


Attribute Information:

1. Choral ID: corresponding to the file names from (Bach Central)[[Web Link]].
2. Event number: index (starting from 1) of the event inside the chorale.
3-14. Pitch classes: YES/NO depending on whether a given pitch is present.
Pitch classes/attribute correspondence is as follows:
C -> 3
C#/Db -> 4
D -> 5
...
B -> 14
15. Bass: Pitch class of the bass note
16. Meter: integers from 1 to 5. Lower numbers denote less accented events,
higher numbers denote more accented events.
17. Chord label: Chord resonating during the given event.


Relevant Papers:

1. D. P. Radicioni and R. Esposito. Advances in Music Information Retrieval,
chapter BREVE: an HMPerceptron-Based Chord Recognition System. Studies
in Computational Intelligence, Zbigniew W. Ras and Alicja Wieczorkowska
(Editors), Springer, 2010.
2. Esposito, R. and Radicioni, D. P., CarpeDiem: Optimizing the Viterbi
Algorithm and Applications to Supervised Sequential Learning, Journal
of Machine Learning Research, 10(Aug):1851-1880, 2009.



Citation Request:

D. P. Radicioni and R. Esposito. Advances in Music Information Retrieval, chapter BREVE: an HMPerceptron-Based Chord Recognition System. Studies in Computational Intelligence, Zbigniew W. Ras and Alicja Wieczorkowska (Editors), Springer, 2010.


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