Version DOI GitHub repo size License

This is a README file for a data repository originating from the DCML corpus initiative and serves as welcome page for both

For information on how to obtain and use the dataset, please refer to this documentation page.

Antonín Dvořák - Silhouettes (A corpus of annotated scores)#

This corpus of annotated MuseScore files has been created within the DCML corpus initiative and employs the DCML harmony annotation standard. It is one out of nine similar corpora that have been grouped together to An Annotated Corpus of Tonal Piano Music from the Long 19th Century which comes with a data report that is currently in press at Empirical Musicology Review.

Version history#

See the GitHub releases.

Getting the data#

With full version history#

The dataset is version-controlled via git. In order to download the files with all revisions they have gone through, git needs to be installed on your machine. Then you can clone this repository using the command

git clone https://github.com/DCMLab/dvorak_silhouettes.git

Without full version history#

If you are only interested in the current version of the corpus, you can simply download and unpack this ZIP file.

Data Formats#

Each piece in this corpus is represented by four files with identical names, each in its own folder. For example, the first movement has the following files:

  • MS3/op08n01.mscx: Uncompressed MuseScore file including the music and annotation labels.

  • notes/op08n01.tsv: A table of all note heads contained in the score and their relevant features (not each of them represents an onset, some are tied together)

  • measures/op08n01.tsv: A table with relevant information about the measures in the score.

  • harmonies/op08n01.tsv: A list of the included harmony labels (including cadences and phrases) with their positions in the score.

Opening Scores#

After navigating to your local copy, you can open the scores in the folder MS3 with the free and open source score editor MuseScore. Please note that the scores have been edited, annotated and tested with MuseScore 3.6.2. MuseScore 4 has since been released and preliminary tests suggest that it renders them correctly.

Opening TSV files in a spreadsheet#

Tab-separated value (TSV) files are like Comma-separated value (CSV) files and can be opened with most modern text editors. However, for correctly displaying the columns, you might want to use a spreadsheet or an addon for your favourite text editor. When you use a spreadsheet such as Excel, it might annoy you by interpreting fractions as dates. This can be circumvented by using Data --> From Text/CSV or the free alternative LibreOffice Calc. Other than that, TSV data can be loaded with every modern programming language.

Loading TSV files in Python#

Since the TSV files contain null values, lists, fractions, and numbers that are to be treated as strings, you may want to use this code to load any TSV files related to this repository (provided you’re doing it in Python). After a quick pip install -U ms3 (requires Python 3.10) you’ll be able to load any TSV like this:

import ms3

labels = ms3.load_tsv('harmonies/op08n01.tsv')
notes = ms3.load_tsv('notes/op08n01.tsv')

How to read metadata.tsv#

This section explains the meaning of the columns contained in metadata.tsv.

File information#

column

content

fname

name without extension (for referencing related files)

rel_path

relative file path of the score, including extension

subdirectory

folder where the score is located

last_mn

last measure number

last_mn_unfolded

number of measures when playing all repeats

length_qb

length of the piece, measured in quarter notes

length_qb_unfolded

length of the piece when playing all repeats

volta_mcs

measure counts of first and second endings

all_notes_qb

summed up duration of all notes, measured in quarter notes

n_onsets

number of note onsets

n_onset_positions

number of unique note onsets (“slices”)

Composition information#

column

content

composer

composer name

workTitle

work title

composed_start

earliest composition date

composed_end

latest composition date

workNumber

Catalogue number(s)

movementNumber

1, 2, or 3

movementTitle

title of the movement

Score information#

column

content

label_count

number of chord labels

KeySig

key signature(s) (negative = flats, positive = sharps)

TimeSig

time signature(s)

musescore

MuseScore version

source

URL to the first typesetter’s file

typesetter

first typesetter

annotators

creator(s) of the chord labels

reviewers

reviewer(s) of the chord labels

Identifiers#

These columns provide a mapping between multiple identifiers for the sonatas (not for individual movements).

column

content

wikidata

URL of the WikiData item

viaf

URL of the Virtual International Authority File (VIAF) entry

musicbrainz

MusicBrainz identifier

imslp

URL to the wiki page within the International Music Score Library Project (IMSLP)

Generating all TSV files from the scores#

When you have made changes to the scores and want to update the TSV files accordingly, you can use the following command (provided you have pip-installed ms3):

ms3 extract -M -N -X -D # for measures, notes, expanded annotations, and metadata

If, in addition, you want to generate the reviewed scores with out-of-label notes colored in red, you can do

ms3 review -M -N -X -D # for extracting measures, notes, expanded annotations, and metadata

By adding the flag -c to the review command, it will additionally compare the (potentially modified) annotations in the score with the ones currently present in the harmonies TSV files and reflect the comparison in the reviewed scores.

Questions, Suggestions, Corrections, Bug Reports#

For questions, remarks etc., please create an issue and feel free to fork and submit pull requests.

License#

Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0).

Naming convention#

The file names listed in the Overview below refer to the 12 pieces contained in opus number 8.

Overview#

file_name

measures

labels

standard

annotators

reviewers

op08n01

52

80

2.3.0

Daniel Grote (2.1.1), Hanné Becker (2.3.0)

Johannes Hentschel (2.1.1), AN

op08n02

15

67

2.3.0

Daniel Grote (2.1.1), Hanné Becker (2.3.0)

Johannes Hentschel (2.1.1), AN

op08n03

72

238

2.3.0

Daniel Grote (2.1.1), Hanné Becker (2.3.0)

Johannes Hentschel (2.1.1)

op08n04

59

136

2.3.0

Adrian Nagel (2.1.1), Hanné Becker (2.3.0)

Adrian Nagel (2.1.1)

op08n05

80

139

2.3.0

Adrian Nagel (2.1.1), Hanné Becker (2.3.0)

Adrian Nagel (2.1.1)

op08n06

60

113

2.3.0

Adrian Nagel (2.1.1), Hanné Becker (2.3.0)

Adrian Nagel (2.1.1)

op08n07

38

167

2.3.0

Adrian Nagel (2.1.1), Hanné Becker (2.3.0)

Adrian Nagel (2.1.1)

op08n08

57

100

2.3.0

Adrian Nagel (2.1.1), Hanné Becker (2.3.0)

Adrian Nagel (2.1.1.)

op08n09

61

97

2.3.0

Adrian Nagel (2.1.1), Hanné Becker (2.3.0)

Adrian Nagel (2.1.1)

op08n10

58

104

2.3.0

Adrian Nagel (2.1.1), Hanné Becker (2.3.0)

Adrian Nagel (2.1.1)

op08n11

44

88

2.3.0

Adrian Nagel (2.1.1), Hanné Becker (2.3.0)

Adrian Nagel (2.1.1)

op08n12

78

210

2.3.0

Adrian Nagel (2.1.1), Hanné Becker (2.3.0)

Adrian Nagel (2.1.1)

Overview table automatically updated using ms3.

Further information: